Instructions to use IoannisKat1/multilingual-e5-large-new with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use IoannisKat1/multilingual-e5-large-new with sentence-transformers:

from sentence_transformers import SentenceTransformer

model = SentenceTransformer("IoannisKat1/multilingual-e5-large-new")

sentences = [
    "When did the victims give away credentials?",
    "According to the provision of Article 386 paragraph 1 of the Greek Penal Code,\n\n\"Whoever, with the intent to obtain for themselves or another an unlawful pecuniary benefit, causes damage to another’s property by persuading someone to act, omit, or tolerate something through the knowing misrepresentation of false facts as true, or through the unlawful concealment or suppression of true facts, shall be punished by imprisonment of at least three months, and if the damage caused is particularly large, by imprisonment of at least two years.\"\n\nFrom this provision it follows that, for the crime of fraud to be established, the following elements are required:\n\na) The intent of the perpetrator to obtain for themselves or another an unlawful pecuniary benefit, without it being necessary that the benefit actually materialize;\n\nb) The knowing misrepresentation of false facts as true, or the unlawful concealment or suppression of true facts, as a result of which—serving as the causal factor—someone is deceived and proceeds to an act, omission, or acquiescence that is detrimental to themselves or another; and\n\nc) Damage to another person’s property, as defined under civil law, which must be causally linked to the deceptive acts or omissions of the perpetrator. It is not required that the person deceived and the person who suffered the damage be the same individual.\n\nThe term “facts”, within the meaning of the above provision, refers to real circumstances relating to the past or present, and not to those that will occur in the future, such as mere promises or contractual obligations. However, when such promises or obligations are accompanied by false assurances and representations of other false facts referring to the present or the past, in such a manner as to create the impression of future fulfillment based on a false present situation fabricated by the perpetrator, who has already formed the decision not to fulfill their obligation, the crime of fraud is established.\n\nThe term “property” refers to the totality of a person’s economic assets that possess monetary value, while damage to property means its reduction—specifically, the difference between the monetary value the property had before the disposition caused by the fraudulent conduct and the value remaining after it. Property damage exists even if the victim possesses an active claim for restitution.\n\nThe time of commission of the fraud is considered to be the moment when the perpetrator acted and completed their fraudulent conduct, namely when they made the false representations that deceived the victim or a third party. Any subsequent moment at which the victim’s damage actually occurred—thereby completing the fraud—or the time when the victim carried out the harmful act or omission, is irrelevant.",
    "Voice phishing involves manipulating victims over the phone. Attackers pose as bank officials or authorities and use intimidation to extract financial details.\n\nScenario:\n- Victims are coerced into giving away PINs, passwords, or other credentials under false pretenses of legal or financial emergencies.",
    "According to the provision of Article 386 paragraph 1 of the Greek Penal Code,\n\n\"Whoever, with the intent to obtain for themselves or another an unlawful pecuniary benefit, causes damage to another’s property by persuading someone to act, omit, or tolerate something through the knowing misrepresentation of false facts as true, or through the unlawful concealment or suppression of true facts, shall be punished by imprisonment of at least three months, and if the damage caused is particularly large, by imprisonment of at least two years.\"\n\nFrom this provision, it follows that, for the crime of fraud to be established, the following elements are required:\n\na) The intent of the perpetrator to obtain for themselves or another an unlawful pecuniary benefit, without requiring that the benefit actually materialize;\n\nb) The knowing misrepresentation of false facts as true, or the unlawful concealment or suppression of true facts, as a result of which—serving as the causal factor—someone is deceived and performs an act, omission, or acquiescence; and\n\nc) Damage to another’s property, according to civil law, which must be causally connected to the perpetrator’s deceptive acts or omissions. It is not required that the deceived person and the person who suffered the loss be the same.\n\nThe term “facts,” within the meaning of the above provision, refers to real circumstances relating to the past or present, and not to those that will occur in the future, such as mere promises or contractual obligations. However, when such promises or obligations are accompanied by false assurances and representations of other false facts relating to the present or the past, in such a way as to create the impression of future fulfillment, based on a false present situation fabricated by the perpetrator—who has already made the decision not to fulfill their obligation—then the crime of fraud is established.\n\nThe term “property” denotes the totality of a person’s economic assets possessing monetary value, while damage to property refers to its reduction—specifically, the difference between the property’s monetary value before the disposition caused by the fraudulent conduct and its value afterward. Property damage exists even if the victim has an active claim for its restitution.\n\nThe time of commission of fraud is considered to be the moment when the perpetrator acted and completed the deceptive conduct, that is, when they made the false representations which deceived the victim or a third party. Any later time at which the victim’s financial loss occurred—thus completing the fraud—or the time when the harmful act or omission of the deceived person took place, is irrelevant.\n\nThe reference to multiple modes of commission of fraud (i.e., both the misrepresentation of false facts and the concealment of true ones) may create ambiguity and contradiction, unless it is made clear from the overall findings that the offense was committed in one particular manner, and that the reference to the other merely serves to define the intent (mens rea) of the perpetrator—specifically, that the representations were false.\n\nFurthermore, a conviction must contain the specific and well-reasoned justification required by Articles 93 paragraph 3 of the Constitution and 139 of the Code of Criminal Procedure. The absence of such reasoning constitutes grounds for cassation (appeal) under Article 510 paragraph 1(d) of the Code of Criminal Procedure, when the judgment does not set out, with clarity, completeness, and consistency, the factual circumstances established by the evidence, upon which the court based its findings regarding the objective and subjective elements of the offense, the evidence supporting those findings, and the legal reasoning through which those facts were subsumed under the applicable substantive criminal provision.\n\nFor the existence of such reasoning, the explanatory and operative parts of the decision may complement each other, as they form a single, unified whole.\n\nThe existence of intent (dolus) does not generally need to be specially justified, since it is inherent in the will to bring about the factual circumstances constituting the objective elements of the offense, and it is presumed from their realization in each particular case—unless the law requires additional elements for criminal liability, such as the act being committed with knowledge of a specific circumstance (direct intent) or with the pursuit of a further purpose, i.e., the achievement of an additional result (offenses requiring a special subjective element).\n\nFurthermore, under Article 510 paragraph 1(e) of the Code of Criminal Procedure, a misapplication of substantive criminal law also constitutes grounds for cassation. Such misapplication occurs when the trial court incorrectly applies the law to the facts it has found to be true, or when the violation occurs indirectly, namely when the reasoning of the judgment—comprising the combination of its factual and operative parts and relating to the elements and identity of the offense—contains ambiguities, contradictions, or logical gaps, rendering it impossible to verify, on appeal, whether the law was applied correctly. In such cases, the judgment lacks a lawful basis."
]
embeddings = model.encode(sentences)

similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4]

Notebooks
Google Colab
Kaggle

IoannisKat1 commited on Sep 13, 2025

Commit

a80efd7

verified ·

1 Parent(s): 731a827

Add finetuned model

Browse files

Files changed (31) hide show

README.md +0 -0
checkpoint-196/README.md +0 -0
checkpoint-196/model.safetensors +1 -1
checkpoint-196/optimizer.pt +1 -1
checkpoint-196/rng_state.pth +1 -1
checkpoint-196/tokenizer_config.json +0 -7
checkpoint-196/trainer_state.json +576 -576
checkpoint-196/training_args.bin +1 -1
checkpoint-294/README.md +0 -0
checkpoint-294/model.safetensors +1 -1
checkpoint-294/optimizer.pt +1 -1
checkpoint-294/rng_state.pth +1 -1
checkpoint-294/tokenizer_config.json +0 -7
checkpoint-294/trainer_state.json +0 -0
checkpoint-294/training_args.bin +1 -1
checkpoint-98/README.md +0 -0
checkpoint-98/model.safetensors +1 -1
checkpoint-98/optimizer.pt +1 -1
checkpoint-98/rng_state.pth +1 -1
checkpoint-98/tokenizer_config.json +0 -7
checkpoint-98/trainer_state.json +288 -288
checkpoint-98/training_args.bin +1 -1
eval/Information-Retrieval_evaluation_dim_1024_results.csv +3 -6
eval/Information-Retrieval_evaluation_dim_128_results.csv +3 -6
eval/Information-Retrieval_evaluation_dim_256_results.csv +3 -6
eval/Information-Retrieval_evaluation_dim_512_results.csv +3 -6
eval/Information-Retrieval_evaluation_dim_64_results.csv +3 -6
eval/Information-Retrieval_evaluation_dim_768_results.csv +3 -6
model.safetensors +1 -1
tokenizer_config.json +0 -7
training_args.bin +1 -1

README.md CHANGED Viewed

The diff for this file is too large to render. See raw diff

checkpoint-196/README.md CHANGED Viewed

The diff for this file is too large to render. See raw diff

checkpoint-196/model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:86fee9b378922f1db9f68cf51a4941e02dfb183276ac89a16c8edbed98e30b9e
 size 2239607176

 version https://git-lfs.github.com/spec/v1
+oid sha256:484814348bf4fcb085f20060a0b9f52191a31badfba256e9f8fbe9f428f90bb0
 size 2239607176

checkpoint-196/optimizer.pt CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:4c03ddaba15f7dd601cacfb32507cfd2ceb73de3b6a0540a718091ec7eb2e678
 size 4471067142

 version https://git-lfs.github.com/spec/v1
+oid sha256:0c08151ebf618205048df61572e8db5af87c9c5b7778d11bffd1ac1d864c2535
 size 4471067142

checkpoint-196/rng_state.pth CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:aa08bd9dd367cde376d15e8b982d14cd6729eae58ce75d651531d783eb6f5977
 size 14645

 version https://git-lfs.github.com/spec/v1
+oid sha256:073fc248f153339698e571b34766dd922834d7173e0dde5ac471b168f6ab29cc
 size 14645

checkpoint-196/tokenizer_config.json CHANGED Viewed

@@ -47,16 +47,9 @@
   "eos_token": "</s>",
   "extra_special_tokens": {},
   "mask_token": "<mask>",
-  "max_length": 512,
   "model_max_length": 512,
-  "pad_to_multiple_of": null,
   "pad_token": "<pad>",
-  "pad_token_type_id": 0,
-  "padding_side": "right",
   "sep_token": "</s>",
-  "stride": 0,
   "tokenizer_class": "XLMRobertaTokenizer",
-  "truncation_side": "right",
-  "truncation_strategy": "longest_first",
   "unk_token": "<unk>"
 }

   "eos_token": "</s>",
   "extra_special_tokens": {},
   "mask_token": "<mask>",
   "model_max_length": 512,
   "pad_token": "<pad>",
   "sep_token": "</s>",
   "tokenizer_class": "XLMRobertaTokenizer",
   "unk_token": "<unk>"
 }

checkpoint-196/trainer_state.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
   "best_global_step": 98,
-  "best_metric": 0.3312285498294292,
   "best_model_checkpoint": "intfloat/multilingual-e5-large/checkpoint-98",
   "epoch": 2.0,
   "eval_steps": 500,
@@ -11,1569 +11,1569 @@
   "log_history": [
     {
       "epoch": 0.01020408163265306,
-      "grad_norm": 973.273681640625,
       "learning_rate": 0.0,
-      "loss": 15.8588,
       "step": 1
     },
     {
       "epoch": 0.02040816326530612,
-      "grad_norm": 1016.8517456054688,
       "learning_rate": 1.0204081632653061e-07,
-      "loss": 10.7411,
       "step": 2
     },
     {
       "epoch": 0.030612244897959183,
-      "grad_norm": 166.88465881347656,
       "learning_rate": 2.0408163265306121e-07,
-      "loss": 1.3873,
       "step": 3
     },
     {
       "epoch": 0.04081632653061224,
-      "grad_norm": 108.06741333007812,
       "learning_rate": 3.0612244897959183e-07,
-      "loss": 0.9088,
       "step": 4
     },
     {
       "epoch": 0.05102040816326531,
-      "grad_norm": 1.1959134340286255,
       "learning_rate": 4.0816326530612243e-07,
-      "loss": 0.0077,
       "step": 5
     },
     {
       "epoch": 0.061224489795918366,
-      "grad_norm": 130.83908081054688,
       "learning_rate": 5.102040816326531e-07,
-      "loss": 0.6016,
       "step": 6
     },
     {
       "epoch": 0.07142857142857142,
-      "grad_norm": 318.3863525390625,
       "learning_rate": 6.122448979591837e-07,
-      "loss": 1.6714,
       "step": 7
     },
     {
       "epoch": 0.08163265306122448,
-      "grad_norm": 74.26002502441406,
       "learning_rate": 7.142857142857143e-07,
-      "loss": 0.4211,
       "step": 8
     },
     {
       "epoch": 0.09183673469387756,
-      "grad_norm": 32.4500846862793,
       "learning_rate": 8.163265306122449e-07,
-      "loss": 0.1996,
       "step": 9
     },
     {
       "epoch": 0.10204081632653061,
-      "grad_norm": 41.27345275878906,
       "learning_rate": 9.183673469387756e-07,
-      "loss": 0.1895,
       "step": 10
     },
     {
       "epoch": 0.11224489795918367,
-      "grad_norm": 27.35291862487793,
       "learning_rate": 1.0204081632653063e-06,
-      "loss": 0.1358,
       "step": 11
     },
     {
       "epoch": 0.12244897959183673,
-      "grad_norm": 103.75244903564453,
       "learning_rate": 1.122448979591837e-06,
-      "loss": 0.5552,
       "step": 12
     },
     {
       "epoch": 0.1326530612244898,
-      "grad_norm": 155.97923278808594,
       "learning_rate": 1.2244897959183673e-06,
-      "loss": 0.5141,
       "step": 13
     },
     {
       "epoch": 0.14285714285714285,
-      "grad_norm": 53.757484436035156,
       "learning_rate": 1.3265306122448982e-06,
-      "loss": 0.1955,
       "step": 14
     },
     {
       "epoch": 0.15306122448979592,
-      "grad_norm": 175.17491149902344,
       "learning_rate": 1.4285714285714286e-06,
-      "loss": 1.9114,
       "step": 15
     },
     {
       "epoch": 0.16326530612244897,
-      "grad_norm": 49.02252197265625,
       "learning_rate": 1.5306122448979593e-06,
-      "loss": 0.2645,
       "step": 16
     },
     {
       "epoch": 0.17346938775510204,
-      "grad_norm": 999.3756103515625,
       "learning_rate": 1.6326530612244897e-06,
-      "loss": 7.5545,
       "step": 17
     },
     {
       "epoch": 0.1836734693877551,
-      "grad_norm": 149.2627410888672,
       "learning_rate": 1.7346938775510206e-06,
-      "loss": 0.4297,
       "step": 18
     },
     {
       "epoch": 0.19387755102040816,
-      "grad_norm": 204.95181274414062,
       "learning_rate": 1.8367346938775512e-06,
-      "loss": 0.678,
       "step": 19
     },
     {
       "epoch": 0.20408163265306123,
-      "grad_norm": 103.94851684570312,
       "learning_rate": 1.938775510204082e-06,
-      "loss": 0.4634,
       "step": 20
     },
     {
       "epoch": 0.21428571428571427,
-      "grad_norm": 536.7100219726562,
       "learning_rate": 2.0408163265306125e-06,
-      "loss": 4.2252,
       "step": 21
     },
     {
       "epoch": 0.22448979591836735,
-      "grad_norm": 444.44805908203125,
       "learning_rate": 2.1428571428571427e-06,
-      "loss": 3.9985,
       "step": 22
     },
     {
       "epoch": 0.23469387755102042,
-      "grad_norm": 170.50369262695312,
       "learning_rate": 2.244897959183674e-06,
-      "loss": 1.9242,
       "step": 23
     },
     {
       "epoch": 0.24489795918367346,
-      "grad_norm": 626.5487060546875,
       "learning_rate": 2.3469387755102044e-06,
-      "loss": 3.2716,
       "step": 24
     },
     {
       "epoch": 0.25510204081632654,
-      "grad_norm": 51.353050231933594,
       "learning_rate": 2.4489795918367347e-06,
-      "loss": 0.123,
       "step": 25
     },
     {
       "epoch": 0.2653061224489796,
-      "grad_norm": 108.25341796875,
       "learning_rate": 2.5510204081632657e-06,
-      "loss": 1.0011,
       "step": 26
     },
     {
       "epoch": 0.2755102040816326,
-      "grad_norm": 322.83502197265625,
       "learning_rate": 2.6530612244897964e-06,
-      "loss": 3.5846,
       "step": 27
     },
     {
       "epoch": 0.2857142857142857,
-      "grad_norm": 203.38458251953125,
       "learning_rate": 2.7551020408163266e-06,
-      "loss": 1.1365,
       "step": 28
     },
     {
       "epoch": 0.29591836734693877,
-      "grad_norm": 127.78427124023438,
       "learning_rate": 2.8571428571428573e-06,
-      "loss": 0.7149,
       "step": 29
     },
     {
       "epoch": 0.30612244897959184,
-      "grad_norm": 283.67645263671875,
       "learning_rate": 2.959183673469388e-06,
-      "loss": 1.2629,
       "step": 30
     },
     {
       "epoch": 0.3163265306122449,
-      "grad_norm": 82.65542602539062,
       "learning_rate": 3.0612244897959185e-06,
-      "loss": 0.6459,
       "step": 31
     },
     {
       "epoch": 0.32653061224489793,
-      "grad_norm": 42.66185760498047,
       "learning_rate": 3.1632653061224496e-06,
-      "loss": 0.1934,
       "step": 32
     },
     {
       "epoch": 0.336734693877551,
-      "grad_norm": 212.1294708251953,
       "learning_rate": 3.2653061224489794e-06,
-      "loss": 1.4897,
       "step": 33
     },
     {
       "epoch": 0.3469387755102041,
-      "grad_norm": 188.0417022705078,
       "learning_rate": 3.3673469387755105e-06,
-      "loss": 0.8561,
       "step": 34
     },
     {
       "epoch": 0.35714285714285715,
-      "grad_norm": 2.0467610359191895,
       "learning_rate": 3.469387755102041e-06,
-      "loss": 0.0128,
       "step": 35
     },
     {
       "epoch": 0.3673469387755102,
-      "grad_norm": 283.3966979980469,
       "learning_rate": 3.5714285714285718e-06,
-      "loss": 1.4952,
       "step": 36
     },
     {
       "epoch": 0.37755102040816324,
-      "grad_norm": 60.74869155883789,
       "learning_rate": 3.6734693877551024e-06,
-      "loss": 0.3181,
       "step": 37
     },
     {
       "epoch": 0.3877551020408163,
-      "grad_norm": 824.6165771484375,
       "learning_rate": 3.7755102040816327e-06,
-      "loss": 6.3681,
       "step": 38
     },
     {
       "epoch": 0.3979591836734694,
-      "grad_norm": 231.1636962890625,
       "learning_rate": 3.877551020408164e-06,
-      "loss": 1.4487,
       "step": 39
     },
     {
       "epoch": 0.40816326530612246,
-      "grad_norm": 26.46611785888672,
       "learning_rate": 3.979591836734694e-06,
-      "loss": 0.1702,
       "step": 40
     },
     {
       "epoch": 0.41836734693877553,
-      "grad_norm": 75.88525390625,
       "learning_rate": 4.081632653061225e-06,
-      "loss": 0.2513,
       "step": 41
     },
     {
       "epoch": 0.42857142857142855,
-      "grad_norm": 465.83392333984375,
       "learning_rate": 4.183673469387755e-06,
-      "loss": 4.1595,
       "step": 42
     },
     {
       "epoch": 0.4387755102040816,
-      "grad_norm": 306.2772521972656,
       "learning_rate": 4.2857142857142855e-06,
-      "loss": 2.7347,
       "step": 43
     },
     {
       "epoch": 0.4489795918367347,
-      "grad_norm": 488.9759521484375,
       "learning_rate": 4.3877551020408165e-06,
-      "loss": 2.3182,
       "step": 44
     },
     {
       "epoch": 0.45918367346938777,
-      "grad_norm": 355.1698913574219,
       "learning_rate": 4.489795918367348e-06,
-      "loss": 1.3285,
       "step": 45
     },
     {
       "epoch": 0.46938775510204084,
-      "grad_norm": 263.558349609375,
       "learning_rate": 4.591836734693878e-06,
-      "loss": 2.1155,
       "step": 46
     },
     {
       "epoch": 0.47959183673469385,
-      "grad_norm": 9.667963981628418,
       "learning_rate": 4.693877551020409e-06,
-      "loss": 0.0645,
       "step": 47
     },
     {
       "epoch": 0.4897959183673469,
-      "grad_norm": 957.79345703125,
       "learning_rate": 4.795918367346939e-06,
-      "loss": 7.1283,
       "step": 48
     },
     {
       "epoch": 0.5,
-      "grad_norm": 160.0965118408203,
       "learning_rate": 4.897959183673469e-06,
-      "loss": 0.711,
       "step": 49
     },
     {
       "epoch": 0.5102040816326531,
-      "grad_norm": 93.697265625,
       "learning_rate": 5e-06,
-      "loss": 0.4716,
       "step": 50
     },
     {
       "epoch": 0.5204081632653061,
-      "grad_norm": 292.9518737792969,
       "learning_rate": 5.1020408163265315e-06,
-      "loss": 2.2895,
       "step": 51
     },
     {
       "epoch": 0.5306122448979592,
-      "grad_norm": 335.4564514160156,
       "learning_rate": 5.204081632653062e-06,
-      "loss": 1.9235,
       "step": 52
     },
     {
       "epoch": 0.5408163265306123,
-      "grad_norm": 138.63575744628906,
       "learning_rate": 5.306122448979593e-06,
-      "loss": 0.8777,
       "step": 53
     },
     {
       "epoch": 0.5510204081632653,
-      "grad_norm": 1.011594533920288,
       "learning_rate": 5.408163265306123e-06,
-      "loss": 0.0038,
       "step": 54
     },
     {
       "epoch": 0.5612244897959183,
-      "grad_norm": 506.25152587890625,
       "learning_rate": 5.510204081632653e-06,
-      "loss": 1.5598,
       "step": 55
     },
     {
       "epoch": 0.5714285714285714,
-      "grad_norm": 2.2550530433654785,
       "learning_rate": 5.6122448979591834e-06,
-      "loss": 0.0177,
       "step": 56
     },
     {
       "epoch": 0.5816326530612245,
-      "grad_norm": 13.93323802947998,
       "learning_rate": 5.7142857142857145e-06,
-      "loss": 0.0837,
       "step": 57
     },
     {
       "epoch": 0.5918367346938775,
-      "grad_norm": 7.279649257659912,
       "learning_rate": 5.816326530612246e-06,
-      "loss": 0.0429,
       "step": 58
     },
     {
       "epoch": 0.6020408163265306,
-      "grad_norm": 0.9923371076583862,
       "learning_rate": 5.918367346938776e-06,
-      "loss": 0.0071,
       "step": 59
     },
     {
       "epoch": 0.6122448979591837,
-      "grad_norm": 743.8301391601562,
       "learning_rate": 6.020408163265307e-06,
-      "loss": 2.7217,
       "step": 60
     },
     {
       "epoch": 0.6224489795918368,
-      "grad_norm": 227.04403686523438,
       "learning_rate": 6.122448979591837e-06,
-      "loss": 3.9013,
       "step": 61
     },
     {
       "epoch": 0.6326530612244898,
-      "grad_norm": 193.12701416015625,
       "learning_rate": 6.224489795918368e-06,
-      "loss": 1.417,
       "step": 62
     },
     {
       "epoch": 0.6428571428571429,
-      "grad_norm": 642.7814331054688,
       "learning_rate": 6.326530612244899e-06,
-      "loss": 3.5854,
       "step": 63
     },
     {
       "epoch": 0.6530612244897959,
-      "grad_norm": 1007.544189453125,
       "learning_rate": 6.4285714285714295e-06,
-      "loss": 12.918,
       "step": 64
     },
     {
       "epoch": 0.6632653061224489,
-      "grad_norm": 1310.942138671875,
       "learning_rate": 6.530612244897959e-06,
-      "loss": 7.1566,
       "step": 65
     },
     {
       "epoch": 0.673469387755102,
-      "grad_norm": 810.1301879882812,
       "learning_rate": 6.63265306122449e-06,
-      "loss": 3.9897,
       "step": 66
     },
     {
       "epoch": 0.6836734693877551,
-      "grad_norm": 513.1759643554688,
       "learning_rate": 6.734693877551021e-06,
-      "loss": 8.1139,
       "step": 67
     },
     {
       "epoch": 0.6938775510204082,
-      "grad_norm": 1414.8878173828125,
       "learning_rate": 6.836734693877551e-06,
-      "loss": 5.7005,
       "step": 68
     },
     {
       "epoch": 0.7040816326530612,
-      "grad_norm": 31.607126235961914,
       "learning_rate": 6.938775510204082e-06,
-      "loss": 0.1219,
       "step": 69
     },
     {
       "epoch": 0.7142857142857143,
-      "grad_norm": 799.9751586914062,
       "learning_rate": 7.0408163265306125e-06,
-      "loss": 5.7849,
       "step": 70
     },
     {
       "epoch": 0.7244897959183674,
-      "grad_norm": 132.71778869628906,
       "learning_rate": 7.1428571428571436e-06,
-      "loss": 1.0726,
       "step": 71
     },
     {
       "epoch": 0.7346938775510204,
-      "grad_norm": 256.61041259765625,
       "learning_rate": 7.244897959183675e-06,
-      "loss": 1.2599,
       "step": 72
     },
     {
       "epoch": 0.7448979591836735,
-      "grad_norm": 192.0435333251953,
       "learning_rate": 7.346938775510205e-06,
-      "loss": 0.6473,
       "step": 73
     },
     {
       "epoch": 0.7551020408163265,
-      "grad_norm": 293.7915954589844,
       "learning_rate": 7.448979591836736e-06,
-      "loss": 1.0397,
       "step": 74
     },
     {
       "epoch": 0.7653061224489796,
-      "grad_norm": 312.2645263671875,
       "learning_rate": 7.551020408163265e-06,
-      "loss": 1.5555,
       "step": 75
     },
     {
       "epoch": 0.7755102040816326,
-      "grad_norm": 1.417815923690796,
       "learning_rate": 7.653061224489796e-06,
-      "loss": 0.0078,
       "step": 76
     },
     {
       "epoch": 0.7857142857142857,
-      "grad_norm": 1.4391653537750244,
       "learning_rate": 7.755102040816327e-06,
-      "loss": 0.0048,
       "step": 77
     },
     {
       "epoch": 0.7959183673469388,
-      "grad_norm": 5.628185749053955,
       "learning_rate": 7.857142857142858e-06,
-      "loss": 0.0323,
       "step": 78
     },
     {
       "epoch": 0.8061224489795918,
-      "grad_norm": 264.5353698730469,
       "learning_rate": 7.959183673469388e-06,
-      "loss": 1.7425,
       "step": 79
     },
     {
       "epoch": 0.8163265306122449,
-      "grad_norm": 1.5278851985931396,
       "learning_rate": 8.06122448979592e-06,
-      "loss": 0.0035,
       "step": 80
     },
     {
       "epoch": 0.826530612244898,
-      "grad_norm": 932.3336181640625,
       "learning_rate": 8.16326530612245e-06,
-      "loss": 6.4849,
       "step": 81
     },
     {
       "epoch": 0.8367346938775511,
-      "grad_norm": 635.4749145507812,
       "learning_rate": 8.26530612244898e-06,
-      "loss": 4.3767,
       "step": 82
     },
     {
       "epoch": 0.8469387755102041,
-      "grad_norm": 8.875201225280762,
       "learning_rate": 8.36734693877551e-06,
-      "loss": 0.0186,
       "step": 83
     },
     {
       "epoch": 0.8571428571428571,
-      "grad_norm": 0.15500876307487488,
       "learning_rate": 8.469387755102042e-06,
-      "loss": 0.0008,
       "step": 84
     },
     {
       "epoch": 0.8673469387755102,
-      "grad_norm": 269.5357666015625,
       "learning_rate": 8.571428571428571e-06,
-      "loss": 0.8354,
       "step": 85
     },
     {
       "epoch": 0.8775510204081632,
-      "grad_norm": 5.054287910461426,
       "learning_rate": 8.673469387755103e-06,
-      "loss": 0.0162,
       "step": 86
     },
     {
       "epoch": 0.8877551020408163,
-      "grad_norm": 84.90735626220703,
       "learning_rate": 8.775510204081633e-06,
-      "loss": 0.1282,
       "step": 87
     },
     {
       "epoch": 0.8979591836734694,
-      "grad_norm": 81.53719329833984,
       "learning_rate": 8.877551020408163e-06,
-      "loss": 0.4514,
       "step": 88
     },
     {
       "epoch": 0.9081632653061225,
-      "grad_norm": 547.4005126953125,
       "learning_rate": 8.979591836734695e-06,
-      "loss": 4.9103,
       "step": 89
     },
     {
       "epoch": 0.9183673469387755,
-      "grad_norm": 25.792213439941406,
       "learning_rate": 9.081632653061225e-06,
-      "loss": 0.0762,
       "step": 90
     },
     {
       "epoch": 0.9285714285714286,
-      "grad_norm": 10.455421447753906,
       "learning_rate": 9.183673469387756e-06,
-      "loss": 0.0444,
       "step": 91
     },
     {
       "epoch": 0.9387755102040817,
-      "grad_norm": 472.54376220703125,
       "learning_rate": 9.285714285714288e-06,
-      "loss": 1.8609,
       "step": 92
     },
     {
       "epoch": 0.9489795918367347,
-      "grad_norm": 31.092357635498047,
       "learning_rate": 9.387755102040818e-06,
-      "loss": 0.1489,
       "step": 93
     },
     {
       "epoch": 0.9591836734693877,
-      "grad_norm": 231.94151306152344,
       "learning_rate": 9.489795918367348e-06,
-      "loss": 0.5926,
       "step": 94
     },
     {
       "epoch": 0.9693877551020408,
-      "grad_norm": 211.05117797851562,
       "learning_rate": 9.591836734693878e-06,
-      "loss": 0.5344,
       "step": 95
     },
     {
       "epoch": 0.9795918367346939,
-      "grad_norm": 217.01339721679688,
       "learning_rate": 9.693877551020408e-06,
-      "loss": 0.4693,
       "step": 96
     },
     {
       "epoch": 0.9897959183673469,
-      "grad_norm": 1123.96484375,
       "learning_rate": 9.795918367346939e-06,
-      "loss": 9.2282,
       "step": 97
     },
     {
       "epoch": 1.0,
-      "grad_norm": 741.597412109375,
       "learning_rate": 9.89795918367347e-06,
-      "loss": 4.6238,
       "step": 98
     },
     {
       "epoch": 1.0,
-      "eval_dim_1024_cosine_accuracy@1": 0.36235595390524966,
-      "eval_dim_1024_cosine_accuracy@10": 0.4334186939820743,
-      "eval_dim_1024_cosine_accuracy@3": 0.3681177976952625,
-      "eval_dim_1024_cosine_accuracy@5": 0.39308578745198464,
-      "eval_dim_1024_cosine_map@100": 0.45394800707643057,
-      "eval_dim_1024_cosine_mrr@10": 0.37430415828303115,
-      "eval_dim_1024_cosine_ndcg@10": 0.3858809020056271,
-      "eval_dim_1024_cosine_precision@1": 0.36235595390524966,
-      "eval_dim_1024_cosine_precision@10": 0.3176696542893726,
-      "eval_dim_1024_cosine_precision@3": 0.36192915066154496,
-      "eval_dim_1024_cosine_precision@5": 0.35172855313700385,
-      "eval_dim_1024_cosine_recall@1": 0.04346309464734114,
-      "eval_dim_1024_cosine_recall@10": 0.28096984500258326,
-      "eval_dim_1024_cosine_recall@3": 0.12757812796185336,
-      "eval_dim_1024_cosine_recall@5": 0.19200836801442767,
-      "eval_dim_128_cosine_accuracy@1": 0.3085787451984635,
-      "eval_dim_128_cosine_accuracy@10": 0.37964148527528807,
-      "eval_dim_128_cosine_accuracy@3": 0.31241997439180536,
       "eval_dim_128_cosine_accuracy@5": 0.3361075544174136,
-      "eval_dim_128_cosine_map@100": 0.3963095303049961,
-      "eval_dim_128_cosine_mrr@10": 0.3199812511432227,
-      "eval_dim_128_cosine_ndcg@10": 0.3312285498294292,
-      "eval_dim_128_cosine_precision@1": 0.3085787451984635,
-      "eval_dim_128_cosine_precision@10": 0.2752880921895006,
-      "eval_dim_128_cosine_precision@3": 0.3079385403329065,
-      "eval_dim_128_cosine_precision@5": 0.29961587708066584,
-      "eval_dim_128_cosine_recall@1": 0.036297623853982414,
-      "eval_dim_128_cosine_recall@10": 0.24000960695821508,
-      "eval_dim_128_cosine_recall@3": 0.10638786483158841,
-      "eval_dim_128_cosine_recall@5": 0.16032639984514846,
-      "eval_dim_256_cosine_accuracy@1": 0.3437900128040973,
-      "eval_dim_256_cosine_accuracy@10": 0.41101152368758004,
-      "eval_dim_256_cosine_accuracy@3": 0.34763124199743917,
-      "eval_dim_256_cosine_accuracy@5": 0.3764404609475032,
-      "eval_dim_256_cosine_map@100": 0.4298669852983799,
-      "eval_dim_256_cosine_mrr@10": 0.3551361197487955,
-      "eval_dim_256_cosine_ndcg@10": 0.3670052960875804,
-      "eval_dim_256_cosine_precision@1": 0.3437900128040973,
-      "eval_dim_256_cosine_precision@10": 0.3040973111395647,
-      "eval_dim_256_cosine_precision@3": 0.342936406316688,
-      "eval_dim_256_cosine_precision@5": 0.33457106274007686,
-      "eval_dim_256_cosine_recall@1": 0.04013102608834382,
-      "eval_dim_256_cosine_recall@10": 0.2648598688529433,
-      "eval_dim_256_cosine_recall@3": 0.11771735023719074,
-      "eval_dim_256_cosine_recall@5": 0.17837935755014916,
-      "eval_dim_512_cosine_accuracy@1": 0.35979513444302175,
-      "eval_dim_512_cosine_accuracy@10": 0.4334186939820743,
-      "eval_dim_512_cosine_accuracy@3": 0.36555697823303457,
-      "eval_dim_512_cosine_accuracy@5": 0.3911651728553137,
-      "eval_dim_512_cosine_map@100": 0.4476805587612892,
-      "eval_dim_512_cosine_mrr@10": 0.37212542934373866,
-      "eval_dim_512_cosine_ndcg@10": 0.3843750966464458,
-      "eval_dim_512_cosine_precision@1": 0.35979513444302175,
-      "eval_dim_512_cosine_precision@10": 0.3173495518565941,
-      "eval_dim_512_cosine_precision@3": 0.35936833119931705,
-      "eval_dim_512_cosine_precision@5": 0.34967989756722156,
-      "eval_dim_512_cosine_recall@1": 0.04265405128130224,
-      "eval_dim_512_cosine_recall@10": 0.2781876565001863,
-      "eval_dim_512_cosine_recall@3": 0.12523102347193127,
-      "eval_dim_512_cosine_recall@5": 0.18912519336740205,
-      "eval_dim_64_cosine_accuracy@1": 0.2740076824583867,
-      "eval_dim_64_cosine_accuracy@10": 0.3354673495518566,
-      "eval_dim_64_cosine_accuracy@3": 0.27848911651728553,
-      "eval_dim_64_cosine_accuracy@5": 0.30153649167733676,
-      "eval_dim_64_cosine_map@100": 0.3539045084602349,
-      "eval_dim_64_cosine_mrr@10": 0.28429414873076814,
-      "eval_dim_64_cosine_ndcg@10": 0.29402896525927075,
-      "eval_dim_64_cosine_precision@1": 0.2740076824583867,
-      "eval_dim_64_cosine_precision@10": 0.24571062740076827,
-      "eval_dim_64_cosine_precision@3": 0.27315407597097735,
-      "eval_dim_64_cosine_precision@5": 0.2670934699103713,
-      "eval_dim_64_cosine_recall@1": 0.03167890172057568,
-      "eval_dim_64_cosine_recall@10": 0.21092883720941633,
-      "eval_dim_64_cosine_recall@3": 0.09267023360511464,
-      "eval_dim_64_cosine_recall@5": 0.14048625468314752,
-      "eval_dim_768_cosine_accuracy@1": 0.3591549295774648,
-      "eval_dim_768_cosine_accuracy@10": 0.4334186939820743,
-      "eval_dim_768_cosine_accuracy@3": 0.3649167733674776,
-      "eval_dim_768_cosine_accuracy@5": 0.3892445582586428,
-      "eval_dim_768_cosine_map@100": 0.4493001842217619,
-      "eval_dim_768_cosine_mrr@10": 0.37149335406377615,
-      "eval_dim_768_cosine_ndcg@10": 0.38308181752122755,
-      "eval_dim_768_cosine_precision@1": 0.3591549295774648,
-      "eval_dim_768_cosine_precision@10": 0.31670934699103714,
-      "eval_dim_768_cosine_precision@3": 0.3587281263337601,
-      "eval_dim_768_cosine_precision@5": 0.34852752880921894,
-      "eval_dim_768_cosine_recall@1": 0.04250079684114586,
-      "eval_dim_768_cosine_recall@10": 0.27695909667507057,
-      "eval_dim_768_cosine_recall@3": 0.12462187901616553,
-      "eval_dim_768_cosine_recall@5": 0.1875478484365334,
-      "eval_runtime": 99.0843,
       "eval_samples_per_second": 0.0,
-      "eval_sequential_score": 0.29402896525927075,
       "eval_steps_per_second": 0.0,
       "step": 98
     },
     {
       "epoch": 1.010204081632653,
-      "grad_norm": 342.861328125,
       "learning_rate": 1e-05,
-      "loss": 1.9644,
       "step": 99
     },
     {
       "epoch": 1.0204081632653061,
-      "grad_norm": 761.8235473632812,
       "learning_rate": 1.0102040816326531e-05,
-      "loss": 7.4242,
       "step": 100
     },
     {
       "epoch": 1.030612244897959,
-      "grad_norm": 146.39175415039062,
       "learning_rate": 1.0204081632653063e-05,
-      "loss": 0.9592,
       "step": 101
     },
     {
       "epoch": 1.0408163265306123,
-      "grad_norm": 69.37447357177734,
       "learning_rate": 1.0306122448979591e-05,
-      "loss": 0.3051,
       "step": 102
     },
     {
       "epoch": 1.0510204081632653,
-      "grad_norm": 241.93687438964844,
       "learning_rate": 1.0408163265306123e-05,
-      "loss": 0.926,
       "step": 103
     },
     {
       "epoch": 1.0612244897959184,
-      "grad_norm": 13.75313949584961,
       "learning_rate": 1.0510204081632654e-05,
-      "loss": 0.0751,
       "step": 104
     },
     {
       "epoch": 1.0714285714285714,
-      "grad_norm": 1.861573576927185,
       "learning_rate": 1.0612244897959186e-05,
-      "loss": 0.0111,
       "step": 105
     },
     {
       "epoch": 1.0816326530612246,
-      "grad_norm": 1.4446377754211426,
       "learning_rate": 1.0714285714285714e-05,
-      "loss": 0.0072,
       "step": 106
     },
     {
       "epoch": 1.0918367346938775,
-      "grad_norm": 2.217988967895508,
       "learning_rate": 1.0816326530612246e-05,
-      "loss": 0.0107,
       "step": 107
     },
     {
       "epoch": 1.1020408163265305,
-      "grad_norm": 620.331787109375,
       "learning_rate": 1.0918367346938776e-05,
-      "loss": 3.4505,
       "step": 108
     },
     {
       "epoch": 1.1122448979591837,
-      "grad_norm": 1.4038218259811401,
       "learning_rate": 1.1020408163265306e-05,
-      "loss": 0.005,
       "step": 109
     },
     {
       "epoch": 1.1224489795918366,
-      "grad_norm": 46.48203659057617,
       "learning_rate": 1.1122448979591838e-05,
-      "loss": 0.1701,
       "step": 110
     },
     {
       "epoch": 1.1326530612244898,
-      "grad_norm": 6.003911972045898,
       "learning_rate": 1.1224489795918367e-05,
-      "loss": 0.027,
       "step": 111
     },
     {
       "epoch": 1.1428571428571428,
-      "grad_norm": 379.09527587890625,
       "learning_rate": 1.1326530612244899e-05,
-      "loss": 1.3824,
       "step": 112
     },
     {
       "epoch": 1.153061224489796,
-      "grad_norm": 1103.1077880859375,
       "learning_rate": 1.1428571428571429e-05,
-      "loss": 8.1459,
       "step": 113
     },
     {
       "epoch": 1.163265306122449,
-      "grad_norm": 29.499439239501953,
       "learning_rate": 1.1530612244897961e-05,
-      "loss": 0.0917,
       "step": 114
     },
     {
       "epoch": 1.1734693877551021,
-      "grad_norm": 0.06352390348911285,
       "learning_rate": 1.1632653061224491e-05,
-      "loss": 0.0003,
       "step": 115
     },
     {
       "epoch": 1.183673469387755,
-      "grad_norm": 111.55418395996094,
       "learning_rate": 1.1734693877551021e-05,
-      "loss": 0.3716,
       "step": 116
     },
     {
       "epoch": 1.193877551020408,
-      "grad_norm": 32.166500091552734,
       "learning_rate": 1.1836734693877552e-05,
-      "loss": 0.1704,
       "step": 117
     },
     {
       "epoch": 1.2040816326530612,
-      "grad_norm": 870.0745239257812,
       "learning_rate": 1.1938775510204084e-05,
-      "loss": 9.8059,
       "step": 118
     },
     {
       "epoch": 1.2142857142857142,
-      "grad_norm": 139.17662048339844,
       "learning_rate": 1.2040816326530614e-05,
-      "loss": 0.5882,
       "step": 119
     },
     {
       "epoch": 1.2244897959183674,
-      "grad_norm": 28.489713668823242,
       "learning_rate": 1.2142857142857142e-05,
-      "loss": 0.0531,
       "step": 120
     },
     {
       "epoch": 1.2346938775510203,
-      "grad_norm": 0.18062859773635864,
       "learning_rate": 1.2244897959183674e-05,
-      "loss": 0.0005,
       "step": 121
     },
     {
       "epoch": 1.2448979591836735,
-      "grad_norm": 8.26645565032959,
       "learning_rate": 1.2346938775510204e-05,
-      "loss": 0.0314,
       "step": 122
     },
     {
       "epoch": 1.2551020408163265,
-      "grad_norm": 64.67955017089844,
       "learning_rate": 1.2448979591836736e-05,
-      "loss": 0.1811,
       "step": 123
     },
     {
       "epoch": 1.2653061224489797,
-      "grad_norm": 420.44439697265625,
       "learning_rate": 1.2551020408163267e-05,
-      "loss": 2.6136,
       "step": 124
     },
     {
       "epoch": 1.2755102040816326,
-      "grad_norm": 3.5323660373687744,
       "learning_rate": 1.2653061224489798e-05,
-      "loss": 0.0087,
       "step": 125
     },
     {
       "epoch": 1.2857142857142856,
-      "grad_norm": 52.854801177978516,
       "learning_rate": 1.2755102040816327e-05,
-      "loss": 0.1269,
       "step": 126
     },
     {
       "epoch": 1.2959183673469388,
-      "grad_norm": 4.583413124084473,
       "learning_rate": 1.2857142857142859e-05,
-      "loss": 0.0091,
       "step": 127
     },
     {
       "epoch": 1.306122448979592,
-      "grad_norm": 17.20958137512207,
       "learning_rate": 1.2959183673469389e-05,
-      "loss": 0.0467,
       "step": 128
     },
     {
       "epoch": 1.316326530612245,
-      "grad_norm": 8.821357727050781,
       "learning_rate": 1.3061224489795918e-05,
-      "loss": 0.0282,
       "step": 129
     },
     {
       "epoch": 1.3265306122448979,
-      "grad_norm": 0.3024923503398895,
       "learning_rate": 1.316326530612245e-05,
-      "loss": 0.0012,
       "step": 130
     },
     {
       "epoch": 1.336734693877551,
-      "grad_norm": 1110.76513671875,
       "learning_rate": 1.326530612244898e-05,
-      "loss": 3.5135,
       "step": 131
     },
     {
       "epoch": 1.346938775510204,
-      "grad_norm": 4.655632495880127,
       "learning_rate": 1.3367346938775512e-05,
-      "loss": 0.0186,
       "step": 132
     },
     {
       "epoch": 1.3571428571428572,
-      "grad_norm": 641.764404296875,
       "learning_rate": 1.3469387755102042e-05,
-      "loss": 3.2599,
       "step": 133
     },
     {
       "epoch": 1.3673469387755102,
-      "grad_norm": 1076.8260498046875,
       "learning_rate": 1.3571428571428574e-05,
-      "loss": 5.5417,
       "step": 134
     },
     {
       "epoch": 1.3775510204081631,
-      "grad_norm": 0.5416738390922546,
       "learning_rate": 1.3673469387755102e-05,
-      "loss": 0.0019,
       "step": 135
     },
     {
       "epoch": 1.3877551020408163,
-      "grad_norm": 200.03311157226562,
       "learning_rate": 1.3775510204081634e-05,
-      "loss": 0.5649,
       "step": 136
     },
     {
       "epoch": 1.3979591836734695,
-      "grad_norm": 35.22038650512695,
       "learning_rate": 1.3877551020408165e-05,
-      "loss": 0.084,
       "step": 137
     },
     {
       "epoch": 1.4081632653061225,
-      "grad_norm": 141.9106903076172,
       "learning_rate": 1.3979591836734696e-05,
-      "loss": 0.6062,
       "step": 138
     },
     {
       "epoch": 1.4183673469387754,
-      "grad_norm": 15.920783996582031,
       "learning_rate": 1.4081632653061225e-05,
-      "loss": 0.0639,
       "step": 139
     },
     {
       "epoch": 1.4285714285714286,
-      "grad_norm": 206.33274841308594,
       "learning_rate": 1.4183673469387755e-05,
-      "loss": 0.4069,
       "step": 140
     },
     {
       "epoch": 1.4387755102040816,
-      "grad_norm": 51.149173736572266,
       "learning_rate": 1.4285714285714287e-05,
-      "loss": 0.2462,
       "step": 141
     },
     {
       "epoch": 1.4489795918367347,
-      "grad_norm": 658.653564453125,
       "learning_rate": 1.4387755102040817e-05,
-      "loss": 4.9288,
       "step": 142
     },
     {
       "epoch": 1.4591836734693877,
-      "grad_norm": 63.49065399169922,
       "learning_rate": 1.448979591836735e-05,
-      "loss": 0.1852,
       "step": 143
     },
     {
       "epoch": 1.469387755102041,
-      "grad_norm": 1453.699462890625,
       "learning_rate": 1.4591836734693878e-05,
-      "loss": 3.0971,
       "step": 144
     },
     {
       "epoch": 1.4795918367346939,
-      "grad_norm": 499.0628662109375,
       "learning_rate": 1.469387755102041e-05,
-      "loss": 3.787,
       "step": 145
     },
     {
       "epoch": 1.489795918367347,
-      "grad_norm": 253.33152770996094,
       "learning_rate": 1.479591836734694e-05,
-      "loss": 0.8474,
       "step": 146
     },
     {
       "epoch": 1.5,
-      "grad_norm": 0.8343175649642944,
       "learning_rate": 1.4897959183673472e-05,
-      "loss": 0.0028,
       "step": 147
     },
     {
       "epoch": 1.510204081632653,
-      "grad_norm": 38.5785026550293,
       "learning_rate": 1.5000000000000002e-05,
-      "loss": 0.0931,
       "step": 148
     },
     {
       "epoch": 1.5204081632653061,
-      "grad_norm": 563.4974365234375,
       "learning_rate": 1.510204081632653e-05,
-      "loss": 1.8378,
       "step": 149
     },
     {
       "epoch": 1.5306122448979593,
-      "grad_norm": 749.0945434570312,
       "learning_rate": 1.5204081632653063e-05,
-      "loss": 2.6074,
       "step": 150
     },
     {
       "epoch": 1.5408163265306123,
-      "grad_norm": 62.52786636352539,
       "learning_rate": 1.530612244897959e-05,
-      "loss": 0.1441,
       "step": 151
     },
     {
       "epoch": 1.5510204081632653,
-      "grad_norm": 281.54400634765625,
       "learning_rate": 1.5408163265306123e-05,
-      "loss": 0.5622,
       "step": 152
     },
     {
       "epoch": 1.5612244897959182,
-      "grad_norm": 1.1233166456222534,
       "learning_rate": 1.5510204081632655e-05,
-      "loss": 0.0049,
       "step": 153
     },
     {
       "epoch": 1.5714285714285714,
-      "grad_norm": 9.458003044128418,
       "learning_rate": 1.5612244897959187e-05,
-      "loss": 0.0268,
       "step": 154
     },
     {
       "epoch": 1.5816326530612246,
-      "grad_norm": 7.9042439460754395,
       "learning_rate": 1.5714285714285715e-05,
-      "loss": 0.0281,
       "step": 155
     },
     {
       "epoch": 1.5918367346938775,
-      "grad_norm": 402.8667907714844,
       "learning_rate": 1.5816326530612247e-05,
-      "loss": 2.9755,
       "step": 156
     },
     {
       "epoch": 1.6020408163265305,
-      "grad_norm": 359.3101806640625,
       "learning_rate": 1.5918367346938776e-05,
-      "loss": 1.0982,
       "step": 157
     },
     {
       "epoch": 1.6122448979591837,
-      "grad_norm": 26.466707229614258,
       "learning_rate": 1.6020408163265308e-05,
-      "loss": 0.0621,
       "step": 158
     },
     {
       "epoch": 1.6224489795918369,
-      "grad_norm": 472.1581726074219,
       "learning_rate": 1.612244897959184e-05,
-      "loss": 6.9631,
       "step": 159
     },
     {
       "epoch": 1.6326530612244898,
-      "grad_norm": 812.54638671875,
       "learning_rate": 1.6224489795918368e-05,
-      "loss": 4.7216,
       "step": 160
     },
     {
       "epoch": 1.6428571428571428,
-      "grad_norm": 252.12796020507812,
       "learning_rate": 1.63265306122449e-05,
-      "loss": 0.848,
       "step": 161
     },
     {
       "epoch": 1.6530612244897958,
-      "grad_norm": 1087.48828125,
       "learning_rate": 1.642857142857143e-05,
-      "loss": 5.6006,
       "step": 162
     },
     {
       "epoch": 1.663265306122449,
-      "grad_norm": 280.405517578125,
       "learning_rate": 1.653061224489796e-05,
-      "loss": 4.299,
       "step": 163
     },
     {
       "epoch": 1.6734693877551021,
-      "grad_norm": 457.81494140625,
       "learning_rate": 1.6632653061224492e-05,
-      "loss": 2.042,
       "step": 164
     },
     {
       "epoch": 1.683673469387755,
-      "grad_norm": 511.0380859375,
       "learning_rate": 1.673469387755102e-05,
-      "loss": 2.4823,
       "step": 165
     },
     {
       "epoch": 1.693877551020408,
-      "grad_norm": 7.505221366882324,
       "learning_rate": 1.6836734693877553e-05,
-      "loss": 0.0189,
       "step": 166
     },
     {
       "epoch": 1.7040816326530612,
-      "grad_norm": 1.01173734664917,
       "learning_rate": 1.6938775510204085e-05,
-      "loss": 0.0039,
       "step": 167
     },
     {
       "epoch": 1.7142857142857144,
-      "grad_norm": 0.5971992015838623,
       "learning_rate": 1.7040816326530613e-05,
-      "loss": 0.0024,
       "step": 168
     },
     {
       "epoch": 1.7244897959183674,
-      "grad_norm": 505.6401672363281,
       "learning_rate": 1.7142857142857142e-05,
-      "loss": 2.0453,
       "step": 169
     },
     {
       "epoch": 1.7346938775510203,
-      "grad_norm": 4.466002464294434,
       "learning_rate": 1.7244897959183674e-05,
-      "loss": 0.0092,
       "step": 170
     },
     {
       "epoch": 1.7448979591836735,
-      "grad_norm": 1.1195125579833984,
       "learning_rate": 1.7346938775510206e-05,
-      "loss": 0.0029,
       "step": 171
     },
     {
       "epoch": 1.7551020408163265,
-      "grad_norm": 104.82202911376953,
       "learning_rate": 1.7448979591836738e-05,
-      "loss": 0.3271,
       "step": 172
     },
     {
       "epoch": 1.7653061224489797,
-      "grad_norm": 1.860406756401062,
       "learning_rate": 1.7551020408163266e-05,
-      "loss": 0.0054,
       "step": 173
     },
     {
       "epoch": 1.7755102040816326,
-      "grad_norm": 0.044311508536338806,
       "learning_rate": 1.7653061224489798e-05,
-      "loss": 0.0002,
       "step": 174
     },
     {
       "epoch": 1.7857142857142856,
-      "grad_norm": 40.70656204223633,
       "learning_rate": 1.7755102040816327e-05,
-      "loss": 0.0685,
       "step": 175
     },
     {
       "epoch": 1.7959183673469388,
-      "grad_norm": 395.348388671875,
       "learning_rate": 1.785714285714286e-05,
-      "loss": 1.3097,
       "step": 176
     },
     {
       "epoch": 1.806122448979592,
-      "grad_norm": 326.2778015136719,
       "learning_rate": 1.795918367346939e-05,
-      "loss": 1.8817,
       "step": 177
     },
     {
       "epoch": 1.816326530612245,
-      "grad_norm": 41.05072784423828,
       "learning_rate": 1.806122448979592e-05,
-      "loss": 0.2497,
       "step": 178
     },
     {
       "epoch": 1.8265306122448979,
-      "grad_norm": 121.29589080810547,
       "learning_rate": 1.816326530612245e-05,
-      "loss": 0.5822,
       "step": 179
     },
     {
       "epoch": 1.836734693877551,
-      "grad_norm": 711.2618408203125,
       "learning_rate": 1.826530612244898e-05,
-      "loss": 1.8103,
       "step": 180
     },
     {
       "epoch": 1.8469387755102042,
-      "grad_norm": 500.7347106933594,
       "learning_rate": 1.836734693877551e-05,
-      "loss": 1.5506,
       "step": 181
     },
     {
       "epoch": 1.8571428571428572,
-      "grad_norm": 252.05322265625,
       "learning_rate": 1.8469387755102043e-05,
-      "loss": 1.281,
       "step": 182
     },
     {
       "epoch": 1.8673469387755102,
-      "grad_norm": 370.9935302734375,
       "learning_rate": 1.8571428571428575e-05,
-      "loss": 2.8616,
       "step": 183
     },
     {
       "epoch": 1.8775510204081631,
-      "grad_norm": 4.682647705078125,
       "learning_rate": 1.8673469387755104e-05,
-      "loss": 0.0118,
       "step": 184
     },
     {
       "epoch": 1.8877551020408163,
-      "grad_norm": 2.143557548522949,
       "learning_rate": 1.8775510204081636e-05,
-      "loss": 0.0038,
       "step": 185
     },
     {
       "epoch": 1.8979591836734695,
-      "grad_norm": 6.499508857727051,
       "learning_rate": 1.8877551020408164e-05,
-      "loss": 0.0331,
       "step": 186
     },
     {
       "epoch": 1.9081632653061225,
-      "grad_norm": 7.2162089347839355,
       "learning_rate": 1.8979591836734696e-05,
-      "loss": 0.0273,
       "step": 187
     },
     {
       "epoch": 1.9183673469387754,
-      "grad_norm": 23.073841094970703,
       "learning_rate": 1.9081632653061225e-05,
-      "loss": 0.1026,
       "step": 188
     },
     {
       "epoch": 1.9285714285714286,
-      "grad_norm": 48.74525833129883,
       "learning_rate": 1.9183673469387756e-05,
-      "loss": 0.1942,
       "step": 189
     },
     {
       "epoch": 1.9387755102040818,
-      "grad_norm": 384.64678955078125,
       "learning_rate": 1.928571428571429e-05,
-      "loss": 3.4886,
       "step": 190
     },
     {
       "epoch": 1.9489795918367347,
-      "grad_norm": 103.53422546386719,
       "learning_rate": 1.9387755102040817e-05,
-      "loss": 0.628,
       "step": 191
     },
     {
       "epoch": 1.9591836734693877,
-      "grad_norm": 42.5008544921875,
       "learning_rate": 1.948979591836735e-05,
-      "loss": 0.1967,
       "step": 192
     },
     {
       "epoch": 1.9693877551020407,
-      "grad_norm": 145.1553955078125,
       "learning_rate": 1.9591836734693877e-05,
-      "loss": 3.9822,
       "step": 193
     },
     {
       "epoch": 1.9795918367346939,
-      "grad_norm": 0.07428821176290512,
       "learning_rate": 1.969387755102041e-05,
-      "loss": 0.0003,
       "step": 194
     },
     {
       "epoch": 1.989795918367347,
-      "grad_norm": 545.6088256835938,
       "learning_rate": 1.979591836734694e-05,
-      "loss": 3.7309,
       "step": 195
     },
     {
       "epoch": 2.0,
-      "grad_norm": 0.5490627288818359,
       "learning_rate": 1.9897959183673473e-05,
-      "loss": 0.0024,
       "step": 196
     },
     {
       "epoch": 2.0,
-      "eval_dim_1024_cosine_accuracy@1": 0.32522407170294493,
-      "eval_dim_1024_cosine_accuracy@10": 0.3969270166453265,
-      "eval_dim_1024_cosine_accuracy@3": 0.33290653008962867,
-      "eval_dim_1024_cosine_accuracy@5": 0.36043533930857874,
-      "eval_dim_1024_cosine_map@100": 0.4164888021641558,
-      "eval_dim_1024_cosine_mrr@10": 0.33769460195516493,
-      "eval_dim_1024_cosine_ndcg@10": 0.34986350069216465,
-      "eval_dim_1024_cosine_precision@1": 0.32522407170294493,
-      "eval_dim_1024_cosine_precision@10": 0.28361075544174136,
-      "eval_dim_1024_cosine_precision@3": 0.3254374733247973,
-      "eval_dim_1024_cosine_precision@5": 0.31626120358514725,
-      "eval_dim_1024_cosine_recall@1": 0.04113491331982186,
-      "eval_dim_1024_cosine_recall@10": 0.2664549051060991,
-      "eval_dim_1024_cosine_recall@3": 0.12080229545561262,
-      "eval_dim_1024_cosine_recall@5": 0.18183789253196145,
-      "eval_dim_128_cosine_accuracy@1": 0.30217669654289375,
-      "eval_dim_128_cosine_accuracy@10": 0.3546734955185659,
-      "eval_dim_128_cosine_accuracy@3": 0.3072983354673495,
-      "eval_dim_128_cosine_accuracy@5": 0.3265044814340589,
-      "eval_dim_128_cosine_map@100": 0.38014172959059034,
-      "eval_dim_128_cosine_mrr@10": 0.3112729406743488,
-      "eval_dim_128_cosine_ndcg@10": 0.32071443787836906,
-      "eval_dim_128_cosine_precision@1": 0.30217669654289375,
-      "eval_dim_128_cosine_precision@10": 0.26312419974391804,
-      "eval_dim_128_cosine_precision@3": 0.30239009816474605,
-      "eval_dim_128_cosine_precision@5": 0.29359795134443023,
-      "eval_dim_128_cosine_recall@1": 0.03603846894598867,
-      "eval_dim_128_cosine_recall@10": 0.23664446759855584,
-      "eval_dim_128_cosine_recall@3": 0.10607255532328354,
-      "eval_dim_128_cosine_recall@5": 0.15998840334482403,
-      "eval_dim_256_cosine_accuracy@1": 0.31049935979513443,
-      "eval_dim_256_cosine_accuracy@10": 0.3725992317541613,
-      "eval_dim_256_cosine_accuracy@3": 0.31882202304737517,
-      "eval_dim_256_cosine_accuracy@5": 0.34571062740076824,
-      "eval_dim_256_cosine_map@100": 0.3940538127924734,
-      "eval_dim_256_cosine_mrr@10": 0.3219094872263883,
-      "eval_dim_256_cosine_ndcg@10": 0.33365785011470184,
-      "eval_dim_256_cosine_precision@1": 0.31049935979513443,
-      "eval_dim_256_cosine_precision@10": 0.2727272727272727,
-      "eval_dim_256_cosine_precision@3": 0.3109261630388391,
-      "eval_dim_256_cosine_precision@5": 0.3035851472471191,
-      "eval_dim_256_cosine_recall@1": 0.0379038673811849,
-      "eval_dim_256_cosine_recall@10": 0.25061548215235363,
-      "eval_dim_256_cosine_recall@3": 0.11184662439829526,
-      "eval_dim_256_cosine_recall@5": 0.16972372403865282,
-      "eval_dim_512_cosine_accuracy@1": 0.32842509603072984,
-      "eval_dim_512_cosine_accuracy@10": 0.39564660691421255,
-      "eval_dim_512_cosine_accuracy@3": 0.33418693982074266,
-      "eval_dim_512_cosine_accuracy@5": 0.36555697823303457,
-      "eval_dim_512_cosine_map@100": 0.4125328284000196,
-      "eval_dim_512_cosine_mrr@10": 0.34027168058858154,
-      "eval_dim_512_cosine_ndcg@10": 0.3525488928748249,
-      "eval_dim_512_cosine_precision@1": 0.32842509603072984,
-      "eval_dim_512_cosine_precision@10": 0.28693982074263763,
-      "eval_dim_512_cosine_precision@3": 0.3282116944088775,
-      "eval_dim_512_cosine_precision@5": 0.31997439180537773,
-      "eval_dim_512_cosine_recall@1": 0.04071091183465321,
-      "eval_dim_512_cosine_recall@10": 0.2638449444559509,
-      "eval_dim_512_cosine_recall@3": 0.11970757850133786,
-      "eval_dim_512_cosine_recall@5": 0.1806811237454132,
-      "eval_dim_64_cosine_accuracy@1": 0.28040973111395645,
-      "eval_dim_64_cosine_accuracy@10": 0.3348271446862996,
-      "eval_dim_64_cosine_accuracy@3": 0.28297055057618437,
-      "eval_dim_64_cosine_accuracy@5": 0.3072983354673495,
-      "eval_dim_64_cosine_map@100": 0.35085623648833997,
-      "eval_dim_64_cosine_mrr@10": 0.28944678170030247,
-      "eval_dim_64_cosine_ndcg@10": 0.2991224720529457,
-      "eval_dim_64_cosine_precision@1": 0.28040973111395645,
-      "eval_dim_64_cosine_precision@10": 0.24878361075544175,
-      "eval_dim_64_cosine_precision@3": 0.27955612462654716,
-      "eval_dim_64_cosine_precision@5": 0.27247119078105,
-      "eval_dim_64_cosine_recall@1": 0.03187808455878807,
-      "eval_dim_64_cosine_recall@10": 0.2128007008801171,
-      "eval_dim_64_cosine_recall@3": 0.09363361347149868,
-      "eval_dim_64_cosine_recall@5": 0.14192536615474802,
-      "eval_dim_768_cosine_accuracy@1": 0.32970550576184376,
-      "eval_dim_768_cosine_accuracy@10": 0.3994878361075544,
-      "eval_dim_768_cosine_accuracy@3": 0.33418693982074266,
-      "eval_dim_768_cosine_accuracy@5": 0.36427656850192064,
-      "eval_dim_768_cosine_map@100": 0.4160652625925415,
-      "eval_dim_768_cosine_mrr@10": 0.3415124585899229,
-      "eval_dim_768_cosine_ndcg@10": 0.35370573856938964,
-      "eval_dim_768_cosine_precision@1": 0.32970550576184376,
-      "eval_dim_768_cosine_precision@10": 0.2877720870678617,
-      "eval_dim_768_cosine_precision@3": 0.3288518992744345,
-      "eval_dim_768_cosine_precision@5": 0.31997439180537773,
-      "eval_dim_768_cosine_recall@1": 0.040955758827011135,
-      "eval_dim_768_cosine_recall@10": 0.26685683005601735,
-      "eval_dim_768_cosine_recall@3": 0.12009305539695316,
-      "eval_dim_768_cosine_recall@5": 0.18142212378067016,
-      "eval_runtime": 99.167,
       "eval_samples_per_second": 0.0,
-      "eval_sequential_score": 0.2991224720529457,
       "eval_steps_per_second": 0.0,
       "step": 196
     }

 {
   "best_global_step": 98,
+  "best_metric": 0.3299991425713933,
   "best_model_checkpoint": "intfloat/multilingual-e5-large/checkpoint-98",
   "epoch": 2.0,
   "eval_steps": 500,
   "log_history": [
     {
       "epoch": 0.01020408163265306,
+      "grad_norm": 196.63563537597656,
       "learning_rate": 0.0,
+      "loss": 4.0658,
       "step": 1
     },
     {
       "epoch": 0.02040816326530612,
+      "grad_norm": 184.93710327148438,
       "learning_rate": 1.0204081632653061e-07,
+      "loss": 5.2785,
       "step": 2
     },
     {
       "epoch": 0.030612244897959183,
+      "grad_norm": 179.60655212402344,
       "learning_rate": 2.0408163265306121e-07,
+      "loss": 4.349,
       "step": 3
     },
     {
       "epoch": 0.04081632653061224,
+      "grad_norm": 163.9447479248047,
       "learning_rate": 3.0612244897959183e-07,
+      "loss": 3.805,
       "step": 4
     },
     {
       "epoch": 0.05102040816326531,
+      "grad_norm": 164.29776000976562,
       "learning_rate": 4.0816326530612243e-07,
+      "loss": 3.1683,
       "step": 5
     },
     {
       "epoch": 0.061224489795918366,
+      "grad_norm": 209.0354766845703,
       "learning_rate": 5.102040816326531e-07,
+      "loss": 5.3989,
       "step": 6
     },
     {
       "epoch": 0.07142857142857142,
+      "grad_norm": 262.14971923828125,
       "learning_rate": 6.122448979591837e-07,
+      "loss": 8.211,
       "step": 7
     },
     {
       "epoch": 0.08163265306122448,
+      "grad_norm": 188.68443298339844,
       "learning_rate": 7.142857142857143e-07,
+      "loss": 5.3598,
       "step": 8
     },
     {
       "epoch": 0.09183673469387756,
+      "grad_norm": 216.530517578125,
       "learning_rate": 8.163265306122449e-07,
+      "loss": 5.0522,
       "step": 9
     },
     {
       "epoch": 0.10204081632653061,
+      "grad_norm": 231.66384887695312,
       "learning_rate": 9.183673469387756e-07,
+      "loss": 4.4736,
       "step": 10
     },
     {
       "epoch": 0.11224489795918367,
+      "grad_norm": 329.2440490722656,
       "learning_rate": 1.0204081632653063e-06,
+      "loss": 8.3251,
       "step": 11
     },
     {
       "epoch": 0.12244897959183673,
+      "grad_norm": 102.95913696289062,
       "learning_rate": 1.122448979591837e-06,
+      "loss": 2.5822,
       "step": 12
     },
     {
       "epoch": 0.1326530612244898,
+      "grad_norm": 116.47322845458984,
       "learning_rate": 1.2244897959183673e-06,
+      "loss": 2.8464,
       "step": 13
     },
     {
       "epoch": 0.14285714285714285,
+      "grad_norm": 226.98976135253906,
       "learning_rate": 1.3265306122448982e-06,
+      "loss": 5.8915,
       "step": 14
     },
     {
       "epoch": 0.15306122448979592,
+      "grad_norm": 192.4533233642578,
       "learning_rate": 1.4285714285714286e-06,
+      "loss": 7.2637,
       "step": 15
     },
     {
       "epoch": 0.16326530612244897,
+      "grad_norm": 269.7630920410156,
       "learning_rate": 1.5306122448979593e-06,
+      "loss": 7.4234,
       "step": 16
     },
     {
       "epoch": 0.17346938775510204,
+      "grad_norm": 111.28227233886719,
       "learning_rate": 1.6326530612244897e-06,
+      "loss": 2.3787,
       "step": 17
     },
     {
       "epoch": 0.1836734693877551,
+      "grad_norm": 165.55792236328125,
       "learning_rate": 1.7346938775510206e-06,
+      "loss": 3.1947,
       "step": 18
     },
     {
       "epoch": 0.19387755102040816,
+      "grad_norm": 152.33682250976562,
       "learning_rate": 1.8367346938775512e-06,
+      "loss": 3.4787,
       "step": 19
     },
     {
       "epoch": 0.20408163265306123,
+      "grad_norm": 159.368408203125,
       "learning_rate": 1.938775510204082e-06,
+      "loss": 5.1418,
       "step": 20
     },
     {
       "epoch": 0.21428571428571427,
+      "grad_norm": 112.97805786132812,
       "learning_rate": 2.0408163265306125e-06,
+      "loss": 2.3042,
       "step": 21
     },
     {
       "epoch": 0.22448979591836735,
+      "grad_norm": 199.43443298339844,
       "learning_rate": 2.1428571428571427e-06,
+      "loss": 6.6786,
       "step": 22
     },
     {
       "epoch": 0.23469387755102042,
+      "grad_norm": 241.95591735839844,
       "learning_rate": 2.244897959183674e-06,
+      "loss": 6.6721,
       "step": 23
     },
     {
       "epoch": 0.24489795918367346,
+      "grad_norm": 249.65122985839844,
       "learning_rate": 2.3469387755102044e-06,
+      "loss": 4.4896,
       "step": 24
     },
     {
       "epoch": 0.25510204081632654,
+      "grad_norm": 183.51483154296875,
       "learning_rate": 2.4489795918367347e-06,
+      "loss": 3.4416,
       "step": 25
     },
     {
       "epoch": 0.2653061224489796,
+      "grad_norm": 286.1512756347656,
       "learning_rate": 2.5510204081632657e-06,
+      "loss": 7.5134,
       "step": 26
     },
     {
       "epoch": 0.2755102040816326,
+      "grad_norm": 98.32283782958984,
       "learning_rate": 2.6530612244897964e-06,
+      "loss": 1.9577,
       "step": 27
     },
     {
       "epoch": 0.2857142857142857,
+      "grad_norm": 274.64178466796875,
       "learning_rate": 2.7551020408163266e-06,
+      "loss": 4.9552,
       "step": 28
     },
     {
       "epoch": 0.29591836734693877,
+      "grad_norm": 142.77537536621094,
       "learning_rate": 2.8571428571428573e-06,
+      "loss": 2.5202,
       "step": 29
     },
     {
       "epoch": 0.30612244897959184,
+      "grad_norm": 127.23304748535156,
       "learning_rate": 2.959183673469388e-06,
+      "loss": 2.4486,
       "step": 30
     },
     {
       "epoch": 0.3163265306122449,
+      "grad_norm": 99.88568878173828,
       "learning_rate": 3.0612244897959185e-06,
+      "loss": 1.9923,
       "step": 31
     },
     {
       "epoch": 0.32653061224489793,
+      "grad_norm": 151.1445770263672,
       "learning_rate": 3.1632653061224496e-06,
+      "loss": 2.8301,
       "step": 32
     },
     {
       "epoch": 0.336734693877551,
+      "grad_norm": 203.54248046875,
       "learning_rate": 3.2653061224489794e-06,
+      "loss": 3.7414,
       "step": 33
     },
     {
       "epoch": 0.3469387755102041,
+      "grad_norm": 443.4117126464844,
       "learning_rate": 3.3673469387755105e-06,
+      "loss": 5.2738,
       "step": 34
     },
     {
       "epoch": 0.35714285714285715,
+      "grad_norm": 178.9974822998047,
       "learning_rate": 3.469387755102041e-06,
+      "loss": 3.791,
       "step": 35
     },
     {
       "epoch": 0.3673469387755102,
+      "grad_norm": 122.32801818847656,
       "learning_rate": 3.5714285714285718e-06,
+      "loss": 1.9081,
       "step": 36
     },
     {
       "epoch": 0.37755102040816324,
+      "grad_norm": 189.6477813720703,
       "learning_rate": 3.6734693877551024e-06,
+      "loss": 2.4172,
       "step": 37
     },
     {
       "epoch": 0.3877551020408163,
+      "grad_norm": 222.67959594726562,
       "learning_rate": 3.7755102040816327e-06,
+      "loss": 4.0417,
       "step": 38
     },
     {
       "epoch": 0.3979591836734694,
+      "grad_norm": 160.97071838378906,
       "learning_rate": 3.877551020408164e-06,
+      "loss": 3.5591,
       "step": 39
     },
     {
       "epoch": 0.40816326530612246,
+      "grad_norm": 178.01609802246094,
       "learning_rate": 3.979591836734694e-06,
+      "loss": 3.0139,
       "step": 40
     },
     {
       "epoch": 0.41836734693877553,
+      "grad_norm": 142.32168579101562,
       "learning_rate": 4.081632653061225e-06,
+      "loss": 2.4836,
       "step": 41
     },
     {
       "epoch": 0.42857142857142855,
+      "grad_norm": 148.1731719970703,
       "learning_rate": 4.183673469387755e-06,
+      "loss": 2.807,
       "step": 42
     },
     {
       "epoch": 0.4387755102040816,
+      "grad_norm": 152.1929931640625,
       "learning_rate": 4.2857142857142855e-06,
+      "loss": 1.9753,
       "step": 43
     },
     {
       "epoch": 0.4489795918367347,
+      "grad_norm": 219.5394287109375,
       "learning_rate": 4.3877551020408165e-06,
+      "loss": 0.9764,
       "step": 44
     },
     {
       "epoch": 0.45918367346938777,
+      "grad_norm": 95.7768783569336,
       "learning_rate": 4.489795918367348e-06,
+      "loss": 1.1398,
       "step": 45
     },
     {
       "epoch": 0.46938775510204084,
+      "grad_norm": 320.86529541015625,
       "learning_rate": 4.591836734693878e-06,
+      "loss": 6.7812,
       "step": 46
     },
     {
       "epoch": 0.47959183673469385,
+      "grad_norm": 18.277860641479492,
       "learning_rate": 4.693877551020409e-06,
+      "loss": 0.2479,
       "step": 47
     },
     {
       "epoch": 0.4897959183673469,
+      "grad_norm": 405.69024658203125,
       "learning_rate": 4.795918367346939e-06,
+      "loss": 6.041,
       "step": 48
     },
     {
       "epoch": 0.5,
+      "grad_norm": 104.91180419921875,
       "learning_rate": 4.897959183673469e-06,
+      "loss": 1.1839,
       "step": 49
     },
     {
       "epoch": 0.5102040816326531,
+      "grad_norm": 110.48990631103516,
       "learning_rate": 5e-06,
+      "loss": 2.0933,
       "step": 50
     },
     {
       "epoch": 0.5204081632653061,
+      "grad_norm": 135.2900390625,
       "learning_rate": 5.1020408163265315e-06,
+      "loss": 1.8613,
       "step": 51
     },
     {
       "epoch": 0.5306122448979592,
+      "grad_norm": 146.744140625,
       "learning_rate": 5.204081632653062e-06,
+      "loss": 2.9359,
       "step": 52
     },
     {
       "epoch": 0.5408163265306123,
+      "grad_norm": 103.08831787109375,
       "learning_rate": 5.306122448979593e-06,
+      "loss": 1.0129,
       "step": 53
     },
     {
       "epoch": 0.5510204081632653,
+      "grad_norm": 527.3735961914062,
       "learning_rate": 5.408163265306123e-06,
+      "loss": 11.8843,
       "step": 54
     },
     {
       "epoch": 0.5612244897959183,
+      "grad_norm": 374.4621887207031,
       "learning_rate": 5.510204081632653e-06,
+      "loss": 5.8523,
       "step": 55
     },
     {
       "epoch": 0.5714285714285714,
+      "grad_norm": 71.62016296386719,
       "learning_rate": 5.6122448979591834e-06,
+      "loss": 0.832,
       "step": 56
     },
     {
       "epoch": 0.5816326530612245,
+      "grad_norm": 287.0186462402344,
       "learning_rate": 5.7142857142857145e-06,
+      "loss": 3.1778,
       "step": 57
     },
     {
       "epoch": 0.5918367346938775,
+      "grad_norm": 31.022693634033203,
       "learning_rate": 5.816326530612246e-06,
+      "loss": 0.3919,
       "step": 58
     },
     {
       "epoch": 0.6020408163265306,
+      "grad_norm": 412.99176025390625,
       "learning_rate": 5.918367346938776e-06,
+      "loss": 7.2526,
       "step": 59
     },
     {
       "epoch": 0.6122448979591837,
+      "grad_norm": 40.534244537353516,
       "learning_rate": 6.020408163265307e-06,
+      "loss": 0.578,
       "step": 60
     },
     {
       "epoch": 0.6224489795918368,
+      "grad_norm": 226.0243682861328,
       "learning_rate": 6.122448979591837e-06,
+      "loss": 2.5233,
       "step": 61
     },
     {
       "epoch": 0.6326530612244898,
+      "grad_norm": 113.55558013916016,
       "learning_rate": 6.224489795918368e-06,
+      "loss": 1.5694,
       "step": 62
     },
     {
       "epoch": 0.6428571428571429,
+      "grad_norm": 190.6112518310547,
       "learning_rate": 6.326530612244899e-06,
+      "loss": 2.2332,
       "step": 63
     },
     {
       "epoch": 0.6530612244897959,
+      "grad_norm": 391.7434387207031,
       "learning_rate": 6.4285714285714295e-06,
+      "loss": 4.5545,
       "step": 64
     },
     {
       "epoch": 0.6632653061224489,
+      "grad_norm": 214.495361328125,
       "learning_rate": 6.530612244897959e-06,
+      "loss": 1.4804,
       "step": 65
     },
     {
       "epoch": 0.673469387755102,
+      "grad_norm": 62.52560806274414,
       "learning_rate": 6.63265306122449e-06,
+      "loss": 0.4391,
       "step": 66
     },
     {
       "epoch": 0.6836734693877551,
+      "grad_norm": 298.97808837890625,
       "learning_rate": 6.734693877551021e-06,
+      "loss": 3.4715,
       "step": 67
     },
     {
       "epoch": 0.6938775510204082,
+      "grad_norm": 483.84796142578125,
       "learning_rate": 6.836734693877551e-06,
+      "loss": 8.5808,
       "step": 68
     },
     {
       "epoch": 0.7040816326530612,
+      "grad_norm": 482.55743408203125,
       "learning_rate": 6.938775510204082e-06,
+      "loss": 5.6959,
       "step": 69
     },
     {
       "epoch": 0.7142857142857143,
+      "grad_norm": 198.6812744140625,
       "learning_rate": 7.0408163265306125e-06,
+      "loss": 3.8277,
       "step": 70
     },
     {
       "epoch": 0.7244897959183674,
+      "grad_norm": 293.4190673828125,
       "learning_rate": 7.1428571428571436e-06,
+      "loss": 2.1832,
       "step": 71
     },
     {
       "epoch": 0.7346938775510204,
+      "grad_norm": 13.164139747619629,
       "learning_rate": 7.244897959183675e-06,
+      "loss": 0.1244,
       "step": 72
     },
     {
       "epoch": 0.7448979591836735,
+      "grad_norm": 163.4252166748047,
       "learning_rate": 7.346938775510205e-06,
+      "loss": 0.7707,
       "step": 73
     },
     {
       "epoch": 0.7551020408163265,
+      "grad_norm": 193.64401245117188,
       "learning_rate": 7.448979591836736e-06,
+      "loss": 3.4828,
       "step": 74
     },
     {
       "epoch": 0.7653061224489796,
+      "grad_norm": 178.31982421875,
       "learning_rate": 7.551020408163265e-06,
+      "loss": 2.9645,
       "step": 75
     },
     {
       "epoch": 0.7755102040816326,
+      "grad_norm": 28.57689666748047,
       "learning_rate": 7.653061224489796e-06,
+      "loss": 0.2948,
       "step": 76
     },
     {
       "epoch": 0.7857142857142857,
+      "grad_norm": 608.8088989257812,
       "learning_rate": 7.755102040816327e-06,
+      "loss": 12.6456,
       "step": 77
     },
     {
       "epoch": 0.7959183673469388,
+      "grad_norm": 123.08556365966797,
       "learning_rate": 7.857142857142858e-06,
+      "loss": 1.2493,
       "step": 78
     },
     {
       "epoch": 0.8061224489795918,
+      "grad_norm": 225.3292694091797,
       "learning_rate": 7.959183673469388e-06,
+      "loss": 2.6675,
       "step": 79
     },
     {
       "epoch": 0.8163265306122449,
+      "grad_norm": 57.49665069580078,
       "learning_rate": 8.06122448979592e-06,
+      "loss": 0.5642,
       "step": 80
     },
     {
       "epoch": 0.826530612244898,
+      "grad_norm": 247.52210998535156,
       "learning_rate": 8.16326530612245e-06,
+      "loss": 1.6008,
       "step": 81
     },
     {
       "epoch": 0.8367346938775511,
+      "grad_norm": 309.60382080078125,
       "learning_rate": 8.26530612244898e-06,
+      "loss": 3.257,
       "step": 82
     },
     {
       "epoch": 0.8469387755102041,
+      "grad_norm": 183.82882690429688,
       "learning_rate": 8.36734693877551e-06,
+      "loss": 2.8086,
       "step": 83
     },
     {
       "epoch": 0.8571428571428571,
+      "grad_norm": 88.08740234375,
       "learning_rate": 8.469387755102042e-06,
+      "loss": 0.4056,
       "step": 84
     },
     {
       "epoch": 0.8673469387755102,
+      "grad_norm": 515.5130615234375,
       "learning_rate": 8.571428571428571e-06,
+      "loss": 3.711,
       "step": 85
     },
     {
       "epoch": 0.8775510204081632,
+      "grad_norm": 2.946629285812378,
       "learning_rate": 8.673469387755103e-06,
+      "loss": 0.0253,
       "step": 86
     },
     {
       "epoch": 0.8877551020408163,
+      "grad_norm": 31.143714904785156,
       "learning_rate": 8.775510204081633e-06,
+      "loss": 0.168,
       "step": 87
     },
     {
       "epoch": 0.8979591836734694,
+      "grad_norm": 535.6795043945312,
       "learning_rate": 8.877551020408163e-06,
+      "loss": 5.0992,
       "step": 88
     },
     {
       "epoch": 0.9081632653061225,
+      "grad_norm": 577.0897216796875,
       "learning_rate": 8.979591836734695e-06,
+      "loss": 5.3724,
       "step": 89
     },
     {
       "epoch": 0.9183673469387755,
+      "grad_norm": 102.31855773925781,
       "learning_rate": 9.081632653061225e-06,
+      "loss": 0.9172,
       "step": 90
     },
     {
       "epoch": 0.9285714285714286,
+      "grad_norm": 306.1739196777344,
       "learning_rate": 9.183673469387756e-06,
+      "loss": 3.1239,
       "step": 91
     },
     {
       "epoch": 0.9387755102040817,
+      "grad_norm": 191.27415466308594,
       "learning_rate": 9.285714285714288e-06,
+      "loss": 1.4121,
       "step": 92
     },
     {
       "epoch": 0.9489795918367347,
+      "grad_norm": 67.19822692871094,
       "learning_rate": 9.387755102040818e-06,
+      "loss": 0.2599,
       "step": 93
     },
     {
       "epoch": 0.9591836734693877,
+      "grad_norm": 17.93955421447754,
       "learning_rate": 9.489795918367348e-06,
+      "loss": 0.1166,
       "step": 94
     },
     {
       "epoch": 0.9693877551020408,
+      "grad_norm": 23.839630126953125,
       "learning_rate": 9.591836734693878e-06,
+      "loss": 0.1938,
       "step": 95
     },
     {
       "epoch": 0.9795918367346939,
+      "grad_norm": 1459.8140869140625,
       "learning_rate": 9.693877551020408e-06,
+      "loss": 18.5143,
       "step": 96
     },
     {
       "epoch": 0.9897959183673469,
+      "grad_norm": 670.869140625,
       "learning_rate": 9.795918367346939e-06,
+      "loss": 6.1932,
       "step": 97
     },
     {
       "epoch": 1.0,
+      "grad_norm": 942.95849609375,
       "learning_rate": 9.89795918367347e-06,
+      "loss": 20.3042,
       "step": 98
     },
     {
       "epoch": 1.0,
+      "eval_dim_1024_cosine_accuracy@1": 0.3719590268886043,
+      "eval_dim_1024_cosine_accuracy@10": 0.43982074263764404,
+      "eval_dim_1024_cosine_accuracy@3": 0.37836107554417414,
+      "eval_dim_1024_cosine_accuracy@5": 0.4020486555697823,
+      "eval_dim_1024_cosine_map@100": 0.4604070214987707,
+      "eval_dim_1024_cosine_mrr@10": 0.383397099770339,
+      "eval_dim_1024_cosine_ndcg@10": 0.3947688545057553,
+      "eval_dim_1024_cosine_precision@1": 0.3719590268886043,
+      "eval_dim_1024_cosine_precision@10": 0.3265044814340589,
+      "eval_dim_1024_cosine_precision@3": 0.37153222364489963,
+      "eval_dim_1024_cosine_precision@5": 0.3613316261203585,
+      "eval_dim_1024_cosine_recall@1": 0.04338670134208909,
+      "eval_dim_1024_cosine_recall@10": 0.28262195979320087,
+      "eval_dim_1024_cosine_recall@3": 0.1268773565773867,
+      "eval_dim_1024_cosine_recall@5": 0.19083511167371434,
+      "eval_dim_128_cosine_accuracy@1": 0.3053777208706786,
+      "eval_dim_128_cosine_accuracy@10": 0.37836107554417414,
+      "eval_dim_128_cosine_accuracy@3": 0.3111395646606914,
       "eval_dim_128_cosine_accuracy@5": 0.3361075544174136,
+      "eval_dim_128_cosine_map@100": 0.3904168259576031,
+      "eval_dim_128_cosine_mrr@10": 0.3174377070503828,
+      "eval_dim_128_cosine_ndcg@10": 0.3299991425713933,
+      "eval_dim_128_cosine_precision@1": 0.3053777208706786,
+      "eval_dim_128_cosine_precision@10": 0.271830985915493,
+      "eval_dim_128_cosine_precision@3": 0.30495091762697396,
+      "eval_dim_128_cosine_precision@5": 0.29641485275288093,
+      "eval_dim_128_cosine_recall@1": 0.03688049871840266,
+      "eval_dim_128_cosine_recall@10": 0.24260019246216608,
+      "eval_dim_128_cosine_recall@3": 0.10779952005618963,
+      "eval_dim_128_cosine_recall@5": 0.16176912684922656,
+      "eval_dim_256_cosine_accuracy@1": 0.324583866837388,
+      "eval_dim_256_cosine_accuracy@10": 0.4058898847631242,
+      "eval_dim_256_cosine_accuracy@3": 0.33290653008962867,
+      "eval_dim_256_cosine_accuracy@5": 0.3649167733674776,
+      "eval_dim_256_cosine_map@100": 0.4232469199200366,
+      "eval_dim_256_cosine_mrr@10": 0.33872299453285326,
+      "eval_dim_256_cosine_ndcg@10": 0.35307499975694673,
+      "eval_dim_256_cosine_precision@1": 0.324583866837388,
+      "eval_dim_256_cosine_precision@10": 0.2935339308578745,
+      "eval_dim_256_cosine_precision@3": 0.324583866837388,
+      "eval_dim_256_cosine_precision@5": 0.31792573623559534,
+      "eval_dim_256_cosine_recall@1": 0.038313787861467184,
+      "eval_dim_256_cosine_recall@10": 0.2549878568107636,
+      "eval_dim_256_cosine_recall@3": 0.11223891931505588,
+      "eval_dim_256_cosine_recall@5": 0.1697408782100328,
+      "eval_dim_512_cosine_accuracy@1": 0.34827144686299616,
+      "eval_dim_512_cosine_accuracy@10": 0.44302176696542894,
+      "eval_dim_512_cosine_accuracy@3": 0.3553137003841229,
+      "eval_dim_512_cosine_accuracy@5": 0.39436619718309857,
+      "eval_dim_512_cosine_map@100": 0.44994622162234726,
+      "eval_dim_512_cosine_mrr@10": 0.3644033392272826,
+      "eval_dim_512_cosine_ndcg@10": 0.3807642678190648,
+      "eval_dim_512_cosine_precision@1": 0.34827144686299616,
+      "eval_dim_512_cosine_precision@10": 0.31798975672215113,
+      "eval_dim_512_cosine_precision@3": 0.34827144686299616,
+      "eval_dim_512_cosine_precision@5": 0.3418693982074264,
+      "eval_dim_512_cosine_recall@1": 0.04125738861359979,
+      "eval_dim_512_cosine_recall@10": 0.2752162089385945,
+      "eval_dim_512_cosine_recall@3": 0.12077279112247459,
+      "eval_dim_512_cosine_recall@5": 0.18268801127884626,
+      "eval_dim_64_cosine_accuracy@1": 0.23175416133162613,
+      "eval_dim_64_cosine_accuracy@10": 0.29833546734955185,
+      "eval_dim_64_cosine_accuracy@3": 0.23879641485275288,
+      "eval_dim_64_cosine_accuracy@5": 0.2612035851472471,
+      "eval_dim_64_cosine_map@100": 0.3151829220617657,
+      "eval_dim_64_cosine_mrr@10": 0.24303802613661746,
+      "eval_dim_64_cosine_ndcg@10": 0.2548721998123125,
+      "eval_dim_64_cosine_precision@1": 0.23175416133162613,
+      "eval_dim_64_cosine_precision@10": 0.20864276568501922,
+      "eval_dim_64_cosine_precision@3": 0.23218096457533077,
+      "eval_dim_64_cosine_precision@5": 0.22740076824583869,
+      "eval_dim_64_cosine_recall@1": 0.028384798943475897,
+      "eval_dim_64_cosine_recall@10": 0.19540887275051927,
+      "eval_dim_64_cosine_recall@3": 0.08325514613360847,
+      "eval_dim_64_cosine_recall@5": 0.12720688223912358,
+      "eval_dim_768_cosine_accuracy@1": 0.36619718309859156,
+      "eval_dim_768_cosine_accuracy@10": 0.44302176696542894,
+      "eval_dim_768_cosine_accuracy@3": 0.37516005121638923,
+      "eval_dim_768_cosine_accuracy@5": 0.4014084507042254,
+      "eval_dim_768_cosine_map@100": 0.4592162636155952,
+      "eval_dim_768_cosine_mrr@10": 0.37943672133812956,
+      "eval_dim_768_cosine_ndcg@10": 0.3923099208699586,
+      "eval_dim_768_cosine_precision@1": 0.36619718309859156,
+      "eval_dim_768_cosine_precision@10": 0.32541613316261203,
+      "eval_dim_768_cosine_precision@3": 0.3666239863422962,
+      "eval_dim_768_cosine_precision@5": 0.35761843790012804,
+      "eval_dim_768_cosine_recall@1": 0.042908107176418055,
+      "eval_dim_768_cosine_recall@10": 0.2828362934197418,
+      "eval_dim_768_cosine_recall@3": 0.12573828441229515,
+      "eval_dim_768_cosine_recall@5": 0.18984022934199501,
+      "eval_runtime": 98.8905,
       "eval_samples_per_second": 0.0,
+      "eval_sequential_score": 0.2548721998123125,
       "eval_steps_per_second": 0.0,
       "step": 98
     },
     {
       "epoch": 1.010204081632653,
+      "grad_norm": 1352.0535888671875,
       "learning_rate": 1e-05,
+      "loss": 2.3413,
       "step": 99
     },
     {
       "epoch": 1.0204081632653061,
+      "grad_norm": 852.8284301757812,
       "learning_rate": 1.0102040816326531e-05,
+      "loss": 9.0759,
       "step": 100
     },
     {
       "epoch": 1.030612244897959,
+      "grad_norm": 13.654555320739746,
       "learning_rate": 1.0204081632653063e-05,
+      "loss": 0.0652,
       "step": 101
     },
     {
       "epoch": 1.0408163265306123,
+      "grad_norm": 725.5890502929688,
       "learning_rate": 1.0306122448979591e-05,
+      "loss": 9.3494,
       "step": 102
     },
     {
       "epoch": 1.0510204081632653,
+      "grad_norm": 42.87101364135742,
       "learning_rate": 1.0408163265306123e-05,
+      "loss": 0.1636,
       "step": 103
     },
     {
       "epoch": 1.0612244897959184,
+      "grad_norm": 366.9559631347656,
       "learning_rate": 1.0510204081632654e-05,
+      "loss": 2.4237,
       "step": 104
     },
     {
       "epoch": 1.0714285714285714,
+      "grad_norm": 332.9723815917969,
       "learning_rate": 1.0612244897959186e-05,
+      "loss": 1.9761,
       "step": 105
     },
     {
       "epoch": 1.0816326530612246,
+      "grad_norm": 512.0596923828125,
       "learning_rate": 1.0714285714285714e-05,
+      "loss": 3.5402,
       "step": 106
     },
     {
       "epoch": 1.0918367346938775,
+      "grad_norm": 199.25193786621094,
       "learning_rate": 1.0816326530612246e-05,
+      "loss": 1.3885,
       "step": 107
     },
     {
       "epoch": 1.1020408163265305,
+      "grad_norm": 300.2743225097656,
       "learning_rate": 1.0918367346938776e-05,
+      "loss": 1.5145,
       "step": 108
     },
     {
       "epoch": 1.1122448979591837,
+      "grad_norm": 382.1838684082031,
       "learning_rate": 1.1020408163265306e-05,
+      "loss": 3.3087,
       "step": 109
     },
     {
       "epoch": 1.1224489795918366,
+      "grad_norm": 164.595703125,
       "learning_rate": 1.1122448979591838e-05,
+      "loss": 0.576,
       "step": 110
     },
     {
       "epoch": 1.1326530612244898,
+      "grad_norm": 184.7035369873047,
       "learning_rate": 1.1224489795918367e-05,
+      "loss": 1.6206,
       "step": 111
     },
     {
       "epoch": 1.1428571428571428,
+      "grad_norm": 811.6741333007812,
       "learning_rate": 1.1326530612244899e-05,
+      "loss": 10.2227,
       "step": 112
     },
     {
       "epoch": 1.153061224489796,
+      "grad_norm": 470.61212158203125,
       "learning_rate": 1.1428571428571429e-05,
+      "loss": 3.1477,
       "step": 113
     },
     {
       "epoch": 1.163265306122449,
+      "grad_norm": 656.7257690429688,
       "learning_rate": 1.1530612244897961e-05,
+      "loss": 2.6782,
       "step": 114
     },
     {
       "epoch": 1.1734693877551021,
+      "grad_norm": 198.0335235595703,
       "learning_rate": 1.1632653061224491e-05,
+      "loss": 1.013,
       "step": 115
     },
     {
       "epoch": 1.183673469387755,
+      "grad_norm": 793.2557373046875,
       "learning_rate": 1.1734693877551021e-05,
+      "loss": 5.486,
       "step": 116
     },
     {
       "epoch": 1.193877551020408,
+      "grad_norm": 40.89669418334961,
       "learning_rate": 1.1836734693877552e-05,
+      "loss": 0.2245,
       "step": 117
     },
     {
       "epoch": 1.2040816326530612,
+      "grad_norm": 215.04872131347656,
       "learning_rate": 1.1938775510204084e-05,
+      "loss": 1.3157,
       "step": 118
     },
     {
       "epoch": 1.2142857142857142,
+      "grad_norm": 10.823179244995117,
       "learning_rate": 1.2040816326530614e-05,
+      "loss": 0.0276,
       "step": 119
     },
     {
       "epoch": 1.2244897959183674,
+      "grad_norm": 150.44537353515625,
       "learning_rate": 1.2142857142857142e-05,
+      "loss": 1.1907,
       "step": 120
     },
     {
       "epoch": 1.2346938775510203,
+      "grad_norm": 21.41417694091797,
       "learning_rate": 1.2244897959183674e-05,
+      "loss": 0.0694,
       "step": 121
     },
     {
       "epoch": 1.2448979591836735,
+      "grad_norm": 185.08053588867188,
       "learning_rate": 1.2346938775510204e-05,
+      "loss": 1.3295,
       "step": 122
     },
     {
       "epoch": 1.2551020408163265,
+      "grad_norm": 123.85110473632812,
       "learning_rate": 1.2448979591836736e-05,
+      "loss": 0.501,
       "step": 123
     },
     {
       "epoch": 1.2653061224489797,
+      "grad_norm": 337.702392578125,
       "learning_rate": 1.2551020408163267e-05,
+      "loss": 2.1739,
       "step": 124
     },
     {
       "epoch": 1.2755102040816326,
+      "grad_norm": 682.425048828125,
       "learning_rate": 1.2653061224489798e-05,
+      "loss": 5.5839,
       "step": 125
     },
     {
       "epoch": 1.2857142857142856,
+      "grad_norm": 182.4869384765625,
       "learning_rate": 1.2755102040816327e-05,
+      "loss": 0.9169,
       "step": 126
     },
     {
       "epoch": 1.2959183673469388,
+      "grad_norm": 87.18023681640625,
       "learning_rate": 1.2857142857142859e-05,
+      "loss": 0.7417,
       "step": 127
     },
     {
       "epoch": 1.306122448979592,
+      "grad_norm": 290.62518310546875,
       "learning_rate": 1.2959183673469389e-05,
+      "loss": 4.4272,
       "step": 128
     },
     {
       "epoch": 1.316326530612245,
+      "grad_norm": 123.35594940185547,
       "learning_rate": 1.3061224489795918e-05,
+      "loss": 1.1165,
       "step": 129
     },
     {
       "epoch": 1.3265306122448979,
+      "grad_norm": 530.7383422851562,
       "learning_rate": 1.316326530612245e-05,
+      "loss": 4.3749,
       "step": 130
     },
     {
       "epoch": 1.336734693877551,
+      "grad_norm": 488.7727966308594,
       "learning_rate": 1.326530612244898e-05,
+      "loss": 4.8529,
       "step": 131
     },
     {
       "epoch": 1.346938775510204,
+      "grad_norm": 912.1464233398438,
       "learning_rate": 1.3367346938775512e-05,
+      "loss": 5.3515,
       "step": 132
     },
     {
       "epoch": 1.3571428571428572,
+      "grad_norm": 3.6914279460906982,
       "learning_rate": 1.3469387755102042e-05,
+      "loss": 0.0201,
       "step": 133
     },
     {
       "epoch": 1.3673469387755102,
+      "grad_norm": 1.16976797580719,
       "learning_rate": 1.3571428571428574e-05,
+      "loss": 0.0088,
       "step": 134
     },
     {
       "epoch": 1.3775510204081631,
+      "grad_norm": 839.4262084960938,
       "learning_rate": 1.3673469387755102e-05,
+      "loss": 2.198,
       "step": 135
     },
     {
       "epoch": 1.3877551020408163,
+      "grad_norm": 2.5965521335601807,
       "learning_rate": 1.3775510204081634e-05,
+      "loss": 0.0158,
       "step": 136
     },
     {
       "epoch": 1.3979591836734695,
+      "grad_norm": 5.312564373016357,
       "learning_rate": 1.3877551020408165e-05,
+      "loss": 0.0304,
       "step": 137
     },
     {
       "epoch": 1.4081632653061225,
+      "grad_norm": 3.9951765537261963,
       "learning_rate": 1.3979591836734696e-05,
+      "loss": 0.0176,
       "step": 138
     },
     {
       "epoch": 1.4183673469387754,
+      "grad_norm": 499.74761962890625,
       "learning_rate": 1.4081632653061225e-05,
+      "loss": 1.9166,
       "step": 139
     },
     {
       "epoch": 1.4285714285714286,
+      "grad_norm": 550.5098266601562,
       "learning_rate": 1.4183673469387755e-05,
+      "loss": 5.8026,
       "step": 140
     },
     {
       "epoch": 1.4387755102040816,
+      "grad_norm": 465.0825500488281,
       "learning_rate": 1.4285714285714287e-05,
+      "loss": 6.2584,
       "step": 141
     },
     {
       "epoch": 1.4489795918367347,
+      "grad_norm": 152.85641479492188,
       "learning_rate": 1.4387755102040817e-05,
+      "loss": 0.6994,
       "step": 142
     },
     {
       "epoch": 1.4591836734693877,
+      "grad_norm": 108.09862518310547,
       "learning_rate": 1.448979591836735e-05,
+      "loss": 0.6583,
       "step": 143
     },
     {
       "epoch": 1.469387755102041,
+      "grad_norm": 9.0764799118042,
       "learning_rate": 1.4591836734693878e-05,
+      "loss": 0.0464,
       "step": 144
     },
     {
       "epoch": 1.4795918367346939,
+      "grad_norm": 162.13211059570312,
       "learning_rate": 1.469387755102041e-05,
+      "loss": 0.8106,
       "step": 145
     },
     {
       "epoch": 1.489795918367347,
+      "grad_norm": 1029.7261962890625,
       "learning_rate": 1.479591836734694e-05,
+      "loss": 14.6794,
       "step": 146
     },
     {
       "epoch": 1.5,
+      "grad_norm": 321.685791015625,
       "learning_rate": 1.4897959183673472e-05,
+      "loss": 1.5998,
       "step": 147
     },
     {
       "epoch": 1.510204081632653,
+      "grad_norm": 22.866291046142578,
       "learning_rate": 1.5000000000000002e-05,
+      "loss": 0.0695,
       "step": 148
     },
     {
       "epoch": 1.5204081632653061,
+      "grad_norm": 188.6576690673828,
       "learning_rate": 1.510204081632653e-05,
+      "loss": 0.9395,
       "step": 149
     },
     {
       "epoch": 1.5306122448979593,
+      "grad_norm": 1417.1654052734375,
       "learning_rate": 1.5204081632653063e-05,
+      "loss": 29.9231,
       "step": 150
     },
     {
       "epoch": 1.5408163265306123,
+      "grad_norm": 1.7937166690826416,
       "learning_rate": 1.530612244897959e-05,
+      "loss": 0.0107,
       "step": 151
     },
     {
       "epoch": 1.5510204081632653,
+      "grad_norm": 6.340953350067139,
       "learning_rate": 1.5408163265306123e-05,
+      "loss": 0.0184,
       "step": 152
     },
     {
       "epoch": 1.5612244897959182,
+      "grad_norm": 11.218599319458008,
       "learning_rate": 1.5510204081632655e-05,
+      "loss": 0.0373,
       "step": 153
     },
     {
       "epoch": 1.5714285714285714,
+      "grad_norm": 164.22007751464844,
       "learning_rate": 1.5612244897959187e-05,
+      "loss": 0.7196,
       "step": 154
     },
     {
       "epoch": 1.5816326530612246,
+      "grad_norm": 173.1319580078125,
       "learning_rate": 1.5714285714285715e-05,
+      "loss": 0.9456,
       "step": 155
     },
     {
       "epoch": 1.5918367346938775,
+      "grad_norm": 337.6502380371094,
       "learning_rate": 1.5816326530612247e-05,
+      "loss": 0.8104,
       "step": 156
     },
     {
       "epoch": 1.6020408163265305,
+      "grad_norm": 429.2533264160156,
       "learning_rate": 1.5918367346938776e-05,
+      "loss": 1.9366,
       "step": 157
     },
     {
       "epoch": 1.6122448979591837,
+      "grad_norm": 877.1956787109375,
       "learning_rate": 1.6020408163265308e-05,
+      "loss": 7.7652,
       "step": 158
     },
     {
       "epoch": 1.6224489795918369,
+      "grad_norm": 113.66088104248047,
       "learning_rate": 1.612244897959184e-05,
+      "loss": 0.521,
       "step": 159
     },
     {
       "epoch": 1.6326530612244898,
+      "grad_norm": 11.550941467285156,
       "learning_rate": 1.6224489795918368e-05,
+      "loss": 0.0238,
       "step": 160
     },
     {
       "epoch": 1.6428571428571428,
+      "grad_norm": 52.35281753540039,
       "learning_rate": 1.63265306122449e-05,
+      "loss": 0.1139,
       "step": 161
     },
     {
       "epoch": 1.6530612244897958,
+      "grad_norm": 137.2505645751953,
       "learning_rate": 1.642857142857143e-05,
+      "loss": 0.5996,
       "step": 162
     },
     {
       "epoch": 1.663265306122449,
+      "grad_norm": 0.7507250905036926,
       "learning_rate": 1.653061224489796e-05,
+      "loss": 0.0036,
       "step": 163
     },
     {
       "epoch": 1.6734693877551021,
+      "grad_norm": 27.53925323486328,
       "learning_rate": 1.6632653061224492e-05,
+      "loss": 0.1499,
       "step": 164
     },
     {
       "epoch": 1.683673469387755,
+      "grad_norm": 169.983154296875,
       "learning_rate": 1.673469387755102e-05,
+      "loss": 0.4617,
       "step": 165
     },
     {
       "epoch": 1.693877551020408,
+      "grad_norm": 30.274919509887695,
       "learning_rate": 1.6836734693877553e-05,
+      "loss": 0.0959,
       "step": 166
     },
     {
       "epoch": 1.7040816326530612,
+      "grad_norm": 38.02618408203125,
       "learning_rate": 1.6938775510204085e-05,
+      "loss": 0.1291,
       "step": 167
     },
     {
       "epoch": 1.7142857142857144,
+      "grad_norm": 0.5495009422302246,
       "learning_rate": 1.7040816326530613e-05,
+      "loss": 0.0018,
       "step": 168
     },
     {
       "epoch": 1.7244897959183674,
+      "grad_norm": 1.4790436029434204,
       "learning_rate": 1.7142857142857142e-05,
+      "loss": 0.0054,
       "step": 169
     },
     {
       "epoch": 1.7346938775510203,
+      "grad_norm": 1496.3338623046875,
       "learning_rate": 1.7244897959183674e-05,
+      "loss": 31.5747,
       "step": 170
     },
     {
       "epoch": 1.7448979591836735,
+      "grad_norm": 88.00984191894531,
       "learning_rate": 1.7346938775510206e-05,
+      "loss": 0.3231,
       "step": 171
     },
     {
       "epoch": 1.7551020408163265,
+      "grad_norm": 436.733642578125,
       "learning_rate": 1.7448979591836738e-05,
+      "loss": 2.5639,
       "step": 172
     },
     {
       "epoch": 1.7653061224489797,
+      "grad_norm": 1169.6356201171875,
       "learning_rate": 1.7551020408163266e-05,
+      "loss": 8.2977,
       "step": 173
     },
     {
       "epoch": 1.7755102040816326,
+      "grad_norm": 97.72107696533203,
       "learning_rate": 1.7653061224489798e-05,
+      "loss": 0.4316,
       "step": 174
     },
     {
       "epoch": 1.7857142857142856,
+      "grad_norm": 12.1145601272583,
       "learning_rate": 1.7755102040816327e-05,
+      "loss": 0.0233,
       "step": 175
     },
     {
       "epoch": 1.7959183673469388,
+      "grad_norm": 203.28208923339844,
       "learning_rate": 1.785714285714286e-05,
+      "loss": 1.0278,
       "step": 176
     },
     {
       "epoch": 1.806122448979592,
+      "grad_norm": 0.141877681016922,
       "learning_rate": 1.795918367346939e-05,
+      "loss": 0.0005,
       "step": 177
     },
     {
       "epoch": 1.816326530612245,
+      "grad_norm": 21.75454330444336,
       "learning_rate": 1.806122448979592e-05,
+      "loss": 0.1203,
       "step": 178
     },
     {
       "epoch": 1.8265306122448979,
+      "grad_norm": 98.08448028564453,
       "learning_rate": 1.816326530612245e-05,
+      "loss": 0.2268,
       "step": 179
     },
     {
       "epoch": 1.836734693877551,
+      "grad_norm": 279.0924377441406,
       "learning_rate": 1.826530612244898e-05,
+      "loss": 3.2014,
       "step": 180
     },
     {
       "epoch": 1.8469387755102042,
+      "grad_norm": 348.4731750488281,
       "learning_rate": 1.836734693877551e-05,
+      "loss": 3.6799,
       "step": 181
     },
     {
       "epoch": 1.8571428571428572,
+      "grad_norm": 77.99913024902344,
       "learning_rate": 1.8469387755102043e-05,
+      "loss": 0.2033,
       "step": 182
     },
     {
       "epoch": 1.8673469387755102,
+      "grad_norm": 144.7059783935547,
       "learning_rate": 1.8571428571428575e-05,
+      "loss": 0.6791,
       "step": 183
     },
     {
       "epoch": 1.8775510204081631,
+      "grad_norm": 914.4169921875,
       "learning_rate": 1.8673469387755104e-05,
+      "loss": 3.14,
       "step": 184
     },
     {
       "epoch": 1.8877551020408163,
+      "grad_norm": 397.94769287109375,
       "learning_rate": 1.8775510204081636e-05,
+      "loss": 0.9216,
       "step": 185
     },
     {
       "epoch": 1.8979591836734695,
+      "grad_norm": 5.423056125640869,
       "learning_rate": 1.8877551020408164e-05,
+      "loss": 0.0194,
       "step": 186
     },
     {
       "epoch": 1.9081632653061225,
+      "grad_norm": 124.5344467163086,
       "learning_rate": 1.8979591836734696e-05,
+      "loss": 0.3126,
       "step": 187
     },
     {
       "epoch": 1.9183673469387754,
+      "grad_norm": 136.97732543945312,
       "learning_rate": 1.9081632653061225e-05,
+      "loss": 0.3414,
       "step": 188
     },
     {
       "epoch": 1.9285714285714286,
+      "grad_norm": 29.086313247680664,
       "learning_rate": 1.9183673469387756e-05,
+      "loss": 0.0684,
       "step": 189
     },
     {
       "epoch": 1.9387755102040818,
+      "grad_norm": 4.842129707336426,
       "learning_rate": 1.928571428571429e-05,
+      "loss": 0.017,
       "step": 190
     },
     {
       "epoch": 1.9489795918367347,
+      "grad_norm": 0.2148096263408661,
       "learning_rate": 1.9387755102040817e-05,
+      "loss": 0.0007,
       "step": 191
     },
     {
       "epoch": 1.9591836734693877,
+      "grad_norm": 63.7159538269043,
       "learning_rate": 1.948979591836735e-05,
+      "loss": 0.2351,
       "step": 192
     },
     {
       "epoch": 1.9693877551020407,
+      "grad_norm": 313.18817138671875,
       "learning_rate": 1.9591836734693877e-05,
+      "loss": 1.9321,
       "step": 193
     },
     {
       "epoch": 1.9795918367346939,
+      "grad_norm": 1025.732177734375,
       "learning_rate": 1.969387755102041e-05,
+      "loss": 5.5642,
       "step": 194
     },
     {
       "epoch": 1.989795918367347,
+      "grad_norm": 603.5271606445312,
       "learning_rate": 1.979591836734694e-05,
+      "loss": 1.3926,
       "step": 195
     },
     {
       "epoch": 2.0,
+      "grad_norm": 6.151113033294678,
       "learning_rate": 1.9897959183673473e-05,
+      "loss": 0.015,
       "step": 196
     },
     {
       "epoch": 2.0,
+      "eval_dim_1024_cosine_accuracy@1": 0.3591549295774648,
+      "eval_dim_1024_cosine_accuracy@10": 0.42445582586427655,
+      "eval_dim_1024_cosine_accuracy@3": 0.3649167733674776,
+      "eval_dim_1024_cosine_accuracy@5": 0.39308578745198464,
+      "eval_dim_1024_cosine_map@100": 0.4442656203645836,
+      "eval_dim_1024_cosine_mrr@10": 0.37061688311688284,
+      "eval_dim_1024_cosine_ndcg@10": 0.38277564232489586,
+      "eval_dim_1024_cosine_precision@1": 0.3591549295774648,
+      "eval_dim_1024_cosine_precision@10": 0.31914212548015364,
+      "eval_dim_1024_cosine_precision@3": 0.35830132309005547,
+      "eval_dim_1024_cosine_precision@5": 0.3495518565941101,
+      "eval_dim_1024_cosine_recall@1": 0.040925664980934,
+      "eval_dim_1024_cosine_recall@10": 0.2663878590041381,
+      "eval_dim_1024_cosine_recall@3": 0.11912044022990924,
+      "eval_dim_1024_cosine_recall@5": 0.17907504115268522,
+      "eval_dim_128_cosine_accuracy@1": 0.3060179257362356,
+      "eval_dim_128_cosine_accuracy@10": 0.3687580025608195,
+      "eval_dim_128_cosine_accuracy@3": 0.31049935979513443,
+      "eval_dim_128_cosine_accuracy@5": 0.3322663252240717,
+      "eval_dim_128_cosine_map@100": 0.38523839229741214,
+      "eval_dim_128_cosine_mrr@10": 0.3164926427250368,
+      "eval_dim_128_cosine_ndcg@10": 0.3273120368593549,
+      "eval_dim_128_cosine_precision@1": 0.3060179257362356,
+      "eval_dim_128_cosine_precision@10": 0.27099871959026883,
+      "eval_dim_128_cosine_precision@3": 0.3053777208706786,
+      "eval_dim_128_cosine_precision@5": 0.29679897567221514,
+      "eval_dim_128_cosine_recall@1": 0.035453426807775947,
+      "eval_dim_128_cosine_recall@10": 0.23154232181544257,
+      "eval_dim_128_cosine_recall@3": 0.10361683841932247,
+      "eval_dim_128_cosine_recall@5": 0.15549008066651587,
+      "eval_dim_256_cosine_accuracy@1": 0.3290653008962868,
+      "eval_dim_256_cosine_accuracy@10": 0.3969270166453265,
+      "eval_dim_256_cosine_accuracy@3": 0.33354673495518566,
+      "eval_dim_256_cosine_accuracy@5": 0.36235595390524966,
+      "eval_dim_256_cosine_map@100": 0.4130430492367209,
+      "eval_dim_256_cosine_mrr@10": 0.3407241428368185,
+      "eval_dim_256_cosine_ndcg@10": 0.3532462927680357,
+      "eval_dim_256_cosine_precision@1": 0.3290653008962868,
+      "eval_dim_256_cosine_precision@10": 0.29423815620998717,
+      "eval_dim_256_cosine_precision@3": 0.3282116944088775,
+      "eval_dim_256_cosine_precision@5": 0.3209987195902689,
+      "eval_dim_256_cosine_recall@1": 0.03735817465789262,
+      "eval_dim_256_cosine_recall@10": 0.24868649598286982,
+      "eval_dim_256_cosine_recall@3": 0.10921822534273136,
+      "eval_dim_256_cosine_recall@5": 0.165931214027115,
+      "eval_dim_512_cosine_accuracy@1": 0.3578745198463508,
+      "eval_dim_512_cosine_accuracy@10": 0.42765685019206146,
+      "eval_dim_512_cosine_accuracy@3": 0.36299615877080665,
+      "eval_dim_512_cosine_accuracy@5": 0.3892445582586428,
+      "eval_dim_512_cosine_map@100": 0.44173422420832625,
+      "eval_dim_512_cosine_mrr@10": 0.36958849053919446,
+      "eval_dim_512_cosine_ndcg@10": 0.3812404238586874,
+      "eval_dim_512_cosine_precision@1": 0.3578745198463508,
+      "eval_dim_512_cosine_precision@10": 0.3177336747759283,
+      "eval_dim_512_cosine_precision@3": 0.35680751173708913,
+      "eval_dim_512_cosine_precision@5": 0.34724711907810496,
+      "eval_dim_512_cosine_recall@1": 0.04087028201741599,
+      "eval_dim_512_cosine_recall@10": 0.2641908975177659,
+      "eval_dim_512_cosine_recall@3": 0.11887426573116062,
+      "eval_dim_512_cosine_recall@5": 0.17823551058609727,
+      "eval_dim_64_cosine_accuracy@1": 0.26504481434058896,
+      "eval_dim_64_cosine_accuracy@10": 0.3322663252240717,
+      "eval_dim_64_cosine_accuracy@3": 0.26952624839948786,
+      "eval_dim_64_cosine_accuracy@5": 0.29257362355953903,
+      "eval_dim_64_cosine_map@100": 0.3471195034779171,
+      "eval_dim_64_cosine_mrr@10": 0.27606167306871515,
+      "eval_dim_64_cosine_ndcg@10": 0.28738876488409937,
+      "eval_dim_64_cosine_precision@1": 0.26504481434058896,
+      "eval_dim_64_cosine_precision@10": 0.2385403329065301,
+      "eval_dim_64_cosine_precision@3": 0.2646180110968843,
+      "eval_dim_64_cosine_precision@5": 0.25813060179257363,
+      "eval_dim_64_cosine_recall@1": 0.030859353047043094,
+      "eval_dim_64_cosine_recall@10": 0.20564514911963047,
+      "eval_dim_64_cosine_recall@3": 0.09025134722734952,
+      "eval_dim_64_cosine_recall@5": 0.13616521781869687,
+      "eval_dim_768_cosine_accuracy@1": 0.3546734955185659,
+      "eval_dim_768_cosine_accuracy@10": 0.4186939820742638,
+      "eval_dim_768_cosine_accuracy@3": 0.36107554417413573,
+      "eval_dim_768_cosine_accuracy@5": 0.3860435339308579,
+      "eval_dim_768_cosine_map@100": 0.4380682423691407,
+      "eval_dim_768_cosine_mrr@10": 0.36586844298111887,
+      "eval_dim_768_cosine_ndcg@10": 0.3776871349900537,
+      "eval_dim_768_cosine_precision@1": 0.3546734955185659,
+      "eval_dim_768_cosine_precision@10": 0.3146606914212548,
+      "eval_dim_768_cosine_precision@3": 0.354033290653009,
+      "eval_dim_768_cosine_precision@5": 0.34494238156209983,
+      "eval_dim_768_cosine_recall@1": 0.04034211902742892,
+      "eval_dim_768_cosine_recall@10": 0.2626701106236,
+      "eval_dim_768_cosine_recall@3": 0.11739647757212558,
+      "eval_dim_768_cosine_recall@5": 0.17629643014791566,
+      "eval_runtime": 98.6366,
       "eval_samples_per_second": 0.0,
+      "eval_sequential_score": 0.28738876488409937,
       "eval_steps_per_second": 0.0,
       "step": 196
     }

checkpoint-196/training_args.bin CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:739b4a0a62fdf782034d2ababe5e5ea588023ed6263f2604e31385fc77a8faab
 size 6097

 version https://git-lfs.github.com/spec/v1
+oid sha256:8a0318feaae2d8aeaebeec5835b4bc77eb79a026385dfb908828064d2f4fd294
 size 6097

checkpoint-294/README.md CHANGED Viewed

The diff for this file is too large to render. See raw diff

checkpoint-294/model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:43c4fc720dc2e3977a3cc3e3497ee115851c08f432984ab97bfaf724a6b3d666
 size 2239607176

 version https://git-lfs.github.com/spec/v1
+oid sha256:78c216aabdfb5d2e5bf950f1cd5a80335096dea547e29ed3b49b85d0858df394
 size 2239607176

checkpoint-294/optimizer.pt CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c0ddd633ecdd2f1e6c3de318b7ceb44fe2f43af2a873c9089a62cd07aaeb5c74
 size 4471067142

 version https://git-lfs.github.com/spec/v1
+oid sha256:82cb9db2c86db21e09c6e695d166b2b80f61223909d1f30787b93eb60455ace8
 size 4471067142

checkpoint-294/rng_state.pth CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5bdc8f1e2d846953d00ba606f4cf92976f5653cd22fea2aacf347840fdb304ea
 size 14645

 version https://git-lfs.github.com/spec/v1
+oid sha256:318bad8325e8be8bdf0a5b272a40b3c1e9ce3b69291a451ca0c924f7dacab8bc
 size 14645

checkpoint-294/tokenizer_config.json CHANGED Viewed

@@ -47,16 +47,9 @@
   "eos_token": "</s>",
   "extra_special_tokens": {},
   "mask_token": "<mask>",
-  "max_length": 512,
   "model_max_length": 512,
-  "pad_to_multiple_of": null,
   "pad_token": "<pad>",
-  "pad_token_type_id": 0,
-  "padding_side": "right",
   "sep_token": "</s>",
-  "stride": 0,
   "tokenizer_class": "XLMRobertaTokenizer",
-  "truncation_side": "right",
-  "truncation_strategy": "longest_first",
   "unk_token": "<unk>"
 }

   "eos_token": "</s>",
   "extra_special_tokens": {},
   "mask_token": "<mask>",
   "model_max_length": 512,
   "pad_token": "<pad>",
   "sep_token": "</s>",
   "tokenizer_class": "XLMRobertaTokenizer",
   "unk_token": "<unk>"
 }

checkpoint-294/trainer_state.json CHANGED Viewed

The diff for this file is too large to render. See raw diff

checkpoint-294/training_args.bin CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:739b4a0a62fdf782034d2ababe5e5ea588023ed6263f2604e31385fc77a8faab
 size 6097

 version https://git-lfs.github.com/spec/v1
+oid sha256:8a0318feaae2d8aeaebeec5835b4bc77eb79a026385dfb908828064d2f4fd294
 size 6097

checkpoint-98/README.md CHANGED Viewed

The diff for this file is too large to render. See raw diff

checkpoint-98/model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b8b8678a200e1ec3a97ec08f700f81cc6660e581d09862b47b576834736c0668
 size 2239607176

 version https://git-lfs.github.com/spec/v1
+oid sha256:ad96896c31a7a57d2d2591979a3de4018f6e0a81c8eb47198774b1b88cd52c55
 size 2239607176

checkpoint-98/optimizer.pt CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:43981d3b1c8c7efd9d147726925594fec137b1d2137148a81f15c7a1d493486a
 size 4471067142

 version https://git-lfs.github.com/spec/v1
+oid sha256:20282c36c7a9cbb242a2f093dea3da6be7e335cb5a7077742e22a6e220d97616
 size 4471067142

checkpoint-98/rng_state.pth CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:a4f05f697e2a026dbb8be0397c5f3215957e05bbf5897dea20c686e5f8917f13
 size 14645

 version https://git-lfs.github.com/spec/v1
+oid sha256:42beaf0575196ccbd002c1b61b2ae1f21df3e7e108abc6b5b6e4c2fc22e71b1d
 size 14645

checkpoint-98/tokenizer_config.json CHANGED Viewed

@@ -47,16 +47,9 @@
   "eos_token": "</s>",
   "extra_special_tokens": {},
   "mask_token": "<mask>",
-  "max_length": 512,
   "model_max_length": 512,
-  "pad_to_multiple_of": null,
   "pad_token": "<pad>",
-  "pad_token_type_id": 0,
-  "padding_side": "right",
   "sep_token": "</s>",
-  "stride": 0,
   "tokenizer_class": "XLMRobertaTokenizer",
-  "truncation_side": "right",
-  "truncation_strategy": "longest_first",
   "unk_token": "<unk>"
 }

   "eos_token": "</s>",
   "extra_special_tokens": {},
   "mask_token": "<mask>",
   "model_max_length": 512,
   "pad_token": "<pad>",
   "sep_token": "</s>",
   "tokenizer_class": "XLMRobertaTokenizer",
   "unk_token": "<unk>"
 }

checkpoint-98/trainer_state.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
   "best_global_step": 98,
-  "best_metric": 0.3312285498294292,
   "best_model_checkpoint": "intfloat/multilingual-e5-large/checkpoint-98",
   "epoch": 1.0,
   "eval_steps": 500,
@@ -11,785 +11,785 @@
   "log_history": [
     {
       "epoch": 0.01020408163265306,
-      "grad_norm": 973.273681640625,
       "learning_rate": 0.0,
-      "loss": 15.8588,
       "step": 1
     },
     {
       "epoch": 0.02040816326530612,
-      "grad_norm": 1016.8517456054688,
       "learning_rate": 1.0204081632653061e-07,
-      "loss": 10.7411,
       "step": 2
     },
     {
       "epoch": 0.030612244897959183,
-      "grad_norm": 166.88465881347656,
       "learning_rate": 2.0408163265306121e-07,
-      "loss": 1.3873,
       "step": 3
     },
     {
       "epoch": 0.04081632653061224,
-      "grad_norm": 108.06741333007812,
       "learning_rate": 3.0612244897959183e-07,
-      "loss": 0.9088,
       "step": 4
     },
     {
       "epoch": 0.05102040816326531,
-      "grad_norm": 1.1959134340286255,
       "learning_rate": 4.0816326530612243e-07,
-      "loss": 0.0077,
       "step": 5
     },
     {
       "epoch": 0.061224489795918366,
-      "grad_norm": 130.83908081054688,
       "learning_rate": 5.102040816326531e-07,
-      "loss": 0.6016,
       "step": 6
     },
     {
       "epoch": 0.07142857142857142,
-      "grad_norm": 318.3863525390625,
       "learning_rate": 6.122448979591837e-07,
-      "loss": 1.6714,
       "step": 7
     },
     {
       "epoch": 0.08163265306122448,
-      "grad_norm": 74.26002502441406,
       "learning_rate": 7.142857142857143e-07,
-      "loss": 0.4211,
       "step": 8
     },
     {
       "epoch": 0.09183673469387756,
-      "grad_norm": 32.4500846862793,
       "learning_rate": 8.163265306122449e-07,
-      "loss": 0.1996,
       "step": 9
     },
     {
       "epoch": 0.10204081632653061,
-      "grad_norm": 41.27345275878906,
       "learning_rate": 9.183673469387756e-07,
-      "loss": 0.1895,
       "step": 10
     },
     {
       "epoch": 0.11224489795918367,
-      "grad_norm": 27.35291862487793,
       "learning_rate": 1.0204081632653063e-06,
-      "loss": 0.1358,
       "step": 11
     },
     {
       "epoch": 0.12244897959183673,
-      "grad_norm": 103.75244903564453,
       "learning_rate": 1.122448979591837e-06,
-      "loss": 0.5552,
       "step": 12
     },
     {
       "epoch": 0.1326530612244898,
-      "grad_norm": 155.97923278808594,
       "learning_rate": 1.2244897959183673e-06,
-      "loss": 0.5141,
       "step": 13
     },
     {
       "epoch": 0.14285714285714285,
-      "grad_norm": 53.757484436035156,
       "learning_rate": 1.3265306122448982e-06,
-      "loss": 0.1955,
       "step": 14
     },
     {
       "epoch": 0.15306122448979592,
-      "grad_norm": 175.17491149902344,
       "learning_rate": 1.4285714285714286e-06,
-      "loss": 1.9114,
       "step": 15
     },
     {
       "epoch": 0.16326530612244897,
-      "grad_norm": 49.02252197265625,
       "learning_rate": 1.5306122448979593e-06,
-      "loss": 0.2645,
       "step": 16
     },
     {
       "epoch": 0.17346938775510204,
-      "grad_norm": 999.3756103515625,
       "learning_rate": 1.6326530612244897e-06,
-      "loss": 7.5545,
       "step": 17
     },
     {
       "epoch": 0.1836734693877551,
-      "grad_norm": 149.2627410888672,
       "learning_rate": 1.7346938775510206e-06,
-      "loss": 0.4297,
       "step": 18
     },
     {
       "epoch": 0.19387755102040816,
-      "grad_norm": 204.95181274414062,
       "learning_rate": 1.8367346938775512e-06,
-      "loss": 0.678,
       "step": 19
     },
     {
       "epoch": 0.20408163265306123,
-      "grad_norm": 103.94851684570312,
       "learning_rate": 1.938775510204082e-06,
-      "loss": 0.4634,
       "step": 20
     },
     {
       "epoch": 0.21428571428571427,
-      "grad_norm": 536.7100219726562,
       "learning_rate": 2.0408163265306125e-06,
-      "loss": 4.2252,
       "step": 21
     },
     {
       "epoch": 0.22448979591836735,
-      "grad_norm": 444.44805908203125,
       "learning_rate": 2.1428571428571427e-06,
-      "loss": 3.9985,
       "step": 22
     },
     {
       "epoch": 0.23469387755102042,
-      "grad_norm": 170.50369262695312,
       "learning_rate": 2.244897959183674e-06,
-      "loss": 1.9242,
       "step": 23
     },
     {
       "epoch": 0.24489795918367346,
-      "grad_norm": 626.5487060546875,
       "learning_rate": 2.3469387755102044e-06,
-      "loss": 3.2716,
       "step": 24
     },
     {
       "epoch": 0.25510204081632654,
-      "grad_norm": 51.353050231933594,
       "learning_rate": 2.4489795918367347e-06,
-      "loss": 0.123,
       "step": 25
     },
     {
       "epoch": 0.2653061224489796,
-      "grad_norm": 108.25341796875,
       "learning_rate": 2.5510204081632657e-06,
-      "loss": 1.0011,
       "step": 26
     },
     {
       "epoch": 0.2755102040816326,
-      "grad_norm": 322.83502197265625,
       "learning_rate": 2.6530612244897964e-06,
-      "loss": 3.5846,
       "step": 27
     },
     {
       "epoch": 0.2857142857142857,
-      "grad_norm": 203.38458251953125,
       "learning_rate": 2.7551020408163266e-06,
-      "loss": 1.1365,
       "step": 28
     },
     {
       "epoch": 0.29591836734693877,
-      "grad_norm": 127.78427124023438,
       "learning_rate": 2.8571428571428573e-06,
-      "loss": 0.7149,
       "step": 29
     },
     {
       "epoch": 0.30612244897959184,
-      "grad_norm": 283.67645263671875,
       "learning_rate": 2.959183673469388e-06,
-      "loss": 1.2629,
       "step": 30
     },
     {
       "epoch": 0.3163265306122449,
-      "grad_norm": 82.65542602539062,
       "learning_rate": 3.0612244897959185e-06,
-      "loss": 0.6459,
       "step": 31
     },
     {
       "epoch": 0.32653061224489793,
-      "grad_norm": 42.66185760498047,
       "learning_rate": 3.1632653061224496e-06,
-      "loss": 0.1934,
       "step": 32
     },
     {
       "epoch": 0.336734693877551,
-      "grad_norm": 212.1294708251953,
       "learning_rate": 3.2653061224489794e-06,
-      "loss": 1.4897,
       "step": 33
     },
     {
       "epoch": 0.3469387755102041,
-      "grad_norm": 188.0417022705078,
       "learning_rate": 3.3673469387755105e-06,
-      "loss": 0.8561,
       "step": 34
     },
     {
       "epoch": 0.35714285714285715,
-      "grad_norm": 2.0467610359191895,
       "learning_rate": 3.469387755102041e-06,
-      "loss": 0.0128,
       "step": 35
     },
     {
       "epoch": 0.3673469387755102,
-      "grad_norm": 283.3966979980469,
       "learning_rate": 3.5714285714285718e-06,
-      "loss": 1.4952,
       "step": 36
     },
     {
       "epoch": 0.37755102040816324,
-      "grad_norm": 60.74869155883789,
       "learning_rate": 3.6734693877551024e-06,
-      "loss": 0.3181,
       "step": 37
     },
     {
       "epoch": 0.3877551020408163,
-      "grad_norm": 824.6165771484375,
       "learning_rate": 3.7755102040816327e-06,
-      "loss": 6.3681,
       "step": 38
     },
     {
       "epoch": 0.3979591836734694,
-      "grad_norm": 231.1636962890625,
       "learning_rate": 3.877551020408164e-06,
-      "loss": 1.4487,
       "step": 39
     },
     {
       "epoch": 0.40816326530612246,
-      "grad_norm": 26.46611785888672,
       "learning_rate": 3.979591836734694e-06,
-      "loss": 0.1702,
       "step": 40
     },
     {
       "epoch": 0.41836734693877553,
-      "grad_norm": 75.88525390625,
       "learning_rate": 4.081632653061225e-06,
-      "loss": 0.2513,
       "step": 41
     },
     {
       "epoch": 0.42857142857142855,
-      "grad_norm": 465.83392333984375,
       "learning_rate": 4.183673469387755e-06,
-      "loss": 4.1595,
       "step": 42
     },
     {
       "epoch": 0.4387755102040816,
-      "grad_norm": 306.2772521972656,
       "learning_rate": 4.2857142857142855e-06,
-      "loss": 2.7347,
       "step": 43
     },
     {
       "epoch": 0.4489795918367347,
-      "grad_norm": 488.9759521484375,
       "learning_rate": 4.3877551020408165e-06,
-      "loss": 2.3182,
       "step": 44
     },
     {
       "epoch": 0.45918367346938777,
-      "grad_norm": 355.1698913574219,
       "learning_rate": 4.489795918367348e-06,
-      "loss": 1.3285,
       "step": 45
     },
     {
       "epoch": 0.46938775510204084,
-      "grad_norm": 263.558349609375,
       "learning_rate": 4.591836734693878e-06,
-      "loss": 2.1155,
       "step": 46
     },
     {
       "epoch": 0.47959183673469385,
-      "grad_norm": 9.667963981628418,
       "learning_rate": 4.693877551020409e-06,
-      "loss": 0.0645,
       "step": 47
     },
     {
       "epoch": 0.4897959183673469,
-      "grad_norm": 957.79345703125,
       "learning_rate": 4.795918367346939e-06,
-      "loss": 7.1283,
       "step": 48
     },
     {
       "epoch": 0.5,
-      "grad_norm": 160.0965118408203,
       "learning_rate": 4.897959183673469e-06,
-      "loss": 0.711,
       "step": 49
     },
     {
       "epoch": 0.5102040816326531,
-      "grad_norm": 93.697265625,
       "learning_rate": 5e-06,
-      "loss": 0.4716,
       "step": 50
     },
     {
       "epoch": 0.5204081632653061,
-      "grad_norm": 292.9518737792969,
       "learning_rate": 5.1020408163265315e-06,
-      "loss": 2.2895,
       "step": 51
     },
     {
       "epoch": 0.5306122448979592,
-      "grad_norm": 335.4564514160156,
       "learning_rate": 5.204081632653062e-06,
-      "loss": 1.9235,
       "step": 52
     },
     {
       "epoch": 0.5408163265306123,
-      "grad_norm": 138.63575744628906,
       "learning_rate": 5.306122448979593e-06,
-      "loss": 0.8777,
       "step": 53
     },
     {
       "epoch": 0.5510204081632653,
-      "grad_norm": 1.011594533920288,
       "learning_rate": 5.408163265306123e-06,
-      "loss": 0.0038,
       "step": 54
     },
     {
       "epoch": 0.5612244897959183,
-      "grad_norm": 506.25152587890625,
       "learning_rate": 5.510204081632653e-06,
-      "loss": 1.5598,
       "step": 55
     },
     {
       "epoch": 0.5714285714285714,
-      "grad_norm": 2.2550530433654785,
       "learning_rate": 5.6122448979591834e-06,
-      "loss": 0.0177,
       "step": 56
     },
     {
       "epoch": 0.5816326530612245,
-      "grad_norm": 13.93323802947998,
       "learning_rate": 5.7142857142857145e-06,
-      "loss": 0.0837,
       "step": 57
     },
     {
       "epoch": 0.5918367346938775,
-      "grad_norm": 7.279649257659912,
       "learning_rate": 5.816326530612246e-06,
-      "loss": 0.0429,
       "step": 58
     },
     {
       "epoch": 0.6020408163265306,
-      "grad_norm": 0.9923371076583862,
       "learning_rate": 5.918367346938776e-06,
-      "loss": 0.0071,
       "step": 59
     },
     {
       "epoch": 0.6122448979591837,
-      "grad_norm": 743.8301391601562,
       "learning_rate": 6.020408163265307e-06,
-      "loss": 2.7217,
       "step": 60
     },
     {
       "epoch": 0.6224489795918368,
-      "grad_norm": 227.04403686523438,
       "learning_rate": 6.122448979591837e-06,
-      "loss": 3.9013,
       "step": 61
     },
     {
       "epoch": 0.6326530612244898,
-      "grad_norm": 193.12701416015625,
       "learning_rate": 6.224489795918368e-06,
-      "loss": 1.417,
       "step": 62
     },
     {
       "epoch": 0.6428571428571429,
-      "grad_norm": 642.7814331054688,
       "learning_rate": 6.326530612244899e-06,
-      "loss": 3.5854,
       "step": 63
     },
     {
       "epoch": 0.6530612244897959,
-      "grad_norm": 1007.544189453125,
       "learning_rate": 6.4285714285714295e-06,
-      "loss": 12.918,
       "step": 64
     },
     {
       "epoch": 0.6632653061224489,
-      "grad_norm": 1310.942138671875,
       "learning_rate": 6.530612244897959e-06,
-      "loss": 7.1566,
       "step": 65
     },
     {
       "epoch": 0.673469387755102,
-      "grad_norm": 810.1301879882812,
       "learning_rate": 6.63265306122449e-06,
-      "loss": 3.9897,
       "step": 66
     },
     {
       "epoch": 0.6836734693877551,
-      "grad_norm": 513.1759643554688,
       "learning_rate": 6.734693877551021e-06,
-      "loss": 8.1139,
       "step": 67
     },
     {
       "epoch": 0.6938775510204082,
-      "grad_norm": 1414.8878173828125,
       "learning_rate": 6.836734693877551e-06,
-      "loss": 5.7005,
       "step": 68
     },
     {
       "epoch": 0.7040816326530612,
-      "grad_norm": 31.607126235961914,
       "learning_rate": 6.938775510204082e-06,
-      "loss": 0.1219,
       "step": 69
     },
     {
       "epoch": 0.7142857142857143,
-      "grad_norm": 799.9751586914062,
       "learning_rate": 7.0408163265306125e-06,
-      "loss": 5.7849,
       "step": 70
     },
     {
       "epoch": 0.7244897959183674,
-      "grad_norm": 132.71778869628906,
       "learning_rate": 7.1428571428571436e-06,
-      "loss": 1.0726,
       "step": 71
     },
     {
       "epoch": 0.7346938775510204,
-      "grad_norm": 256.61041259765625,
       "learning_rate": 7.244897959183675e-06,
-      "loss": 1.2599,
       "step": 72
     },
     {
       "epoch": 0.7448979591836735,
-      "grad_norm": 192.0435333251953,
       "learning_rate": 7.346938775510205e-06,
-      "loss": 0.6473,
       "step": 73
     },
     {
       "epoch": 0.7551020408163265,
-      "grad_norm": 293.7915954589844,
       "learning_rate": 7.448979591836736e-06,
-      "loss": 1.0397,
       "step": 74
     },
     {
       "epoch": 0.7653061224489796,
-      "grad_norm": 312.2645263671875,
       "learning_rate": 7.551020408163265e-06,
-      "loss": 1.5555,
       "step": 75
     },
     {
       "epoch": 0.7755102040816326,
-      "grad_norm": 1.417815923690796,
       "learning_rate": 7.653061224489796e-06,
-      "loss": 0.0078,
       "step": 76
     },
     {
       "epoch": 0.7857142857142857,
-      "grad_norm": 1.4391653537750244,
       "learning_rate": 7.755102040816327e-06,
-      "loss": 0.0048,
       "step": 77
     },
     {
       "epoch": 0.7959183673469388,
-      "grad_norm": 5.628185749053955,
       "learning_rate": 7.857142857142858e-06,
-      "loss": 0.0323,
       "step": 78
     },
     {
       "epoch": 0.8061224489795918,
-      "grad_norm": 264.5353698730469,
       "learning_rate": 7.959183673469388e-06,
-      "loss": 1.7425,
       "step": 79
     },
     {
       "epoch": 0.8163265306122449,
-      "grad_norm": 1.5278851985931396,
       "learning_rate": 8.06122448979592e-06,
-      "loss": 0.0035,
       "step": 80
     },
     {
       "epoch": 0.826530612244898,
-      "grad_norm": 932.3336181640625,
       "learning_rate": 8.16326530612245e-06,
-      "loss": 6.4849,
       "step": 81
     },
     {
       "epoch": 0.8367346938775511,
-      "grad_norm": 635.4749145507812,
       "learning_rate": 8.26530612244898e-06,
-      "loss": 4.3767,
       "step": 82
     },
     {
       "epoch": 0.8469387755102041,
-      "grad_norm": 8.875201225280762,
       "learning_rate": 8.36734693877551e-06,
-      "loss": 0.0186,
       "step": 83
     },
     {
       "epoch": 0.8571428571428571,
-      "grad_norm": 0.15500876307487488,
       "learning_rate": 8.469387755102042e-06,
-      "loss": 0.0008,
       "step": 84
     },
     {
       "epoch": 0.8673469387755102,
-      "grad_norm": 269.5357666015625,
       "learning_rate": 8.571428571428571e-06,
-      "loss": 0.8354,
       "step": 85
     },
     {
       "epoch": 0.8775510204081632,
-      "grad_norm": 5.054287910461426,
       "learning_rate": 8.673469387755103e-06,
-      "loss": 0.0162,
       "step": 86
     },
     {
       "epoch": 0.8877551020408163,
-      "grad_norm": 84.90735626220703,
       "learning_rate": 8.775510204081633e-06,
-      "loss": 0.1282,
       "step": 87
     },
     {
       "epoch": 0.8979591836734694,
-      "grad_norm": 81.53719329833984,
       "learning_rate": 8.877551020408163e-06,
-      "loss": 0.4514,
       "step": 88
     },
     {
       "epoch": 0.9081632653061225,
-      "grad_norm": 547.4005126953125,
       "learning_rate": 8.979591836734695e-06,
-      "loss": 4.9103,
       "step": 89
     },
     {
       "epoch": 0.9183673469387755,
-      "grad_norm": 25.792213439941406,
       "learning_rate": 9.081632653061225e-06,
-      "loss": 0.0762,
       "step": 90
     },
     {
       "epoch": 0.9285714285714286,
-      "grad_norm": 10.455421447753906,
       "learning_rate": 9.183673469387756e-06,
-      "loss": 0.0444,
       "step": 91
     },
     {
       "epoch": 0.9387755102040817,
-      "grad_norm": 472.54376220703125,
       "learning_rate": 9.285714285714288e-06,
-      "loss": 1.8609,
       "step": 92
     },
     {
       "epoch": 0.9489795918367347,
-      "grad_norm": 31.092357635498047,
       "learning_rate": 9.387755102040818e-06,
-      "loss": 0.1489,
       "step": 93
     },
     {
       "epoch": 0.9591836734693877,
-      "grad_norm": 231.94151306152344,
       "learning_rate": 9.489795918367348e-06,
-      "loss": 0.5926,
       "step": 94
     },
     {
       "epoch": 0.9693877551020408,
-      "grad_norm": 211.05117797851562,
       "learning_rate": 9.591836734693878e-06,
-      "loss": 0.5344,
       "step": 95
     },
     {
       "epoch": 0.9795918367346939,
-      "grad_norm": 217.01339721679688,
       "learning_rate": 9.693877551020408e-06,
-      "loss": 0.4693,
       "step": 96
     },
     {
       "epoch": 0.9897959183673469,
-      "grad_norm": 1123.96484375,
       "learning_rate": 9.795918367346939e-06,
-      "loss": 9.2282,
       "step": 97
     },
     {
       "epoch": 1.0,
-      "grad_norm": 741.597412109375,
       "learning_rate": 9.89795918367347e-06,
-      "loss": 4.6238,
       "step": 98
     },
     {
       "epoch": 1.0,
-      "eval_dim_1024_cosine_accuracy@1": 0.36235595390524966,
-      "eval_dim_1024_cosine_accuracy@10": 0.4334186939820743,
-      "eval_dim_1024_cosine_accuracy@3": 0.3681177976952625,
-      "eval_dim_1024_cosine_accuracy@5": 0.39308578745198464,
-      "eval_dim_1024_cosine_map@100": 0.45394800707643057,
-      "eval_dim_1024_cosine_mrr@10": 0.37430415828303115,
-      "eval_dim_1024_cosine_ndcg@10": 0.3858809020056271,
-      "eval_dim_1024_cosine_precision@1": 0.36235595390524966,
-      "eval_dim_1024_cosine_precision@10": 0.3176696542893726,
-      "eval_dim_1024_cosine_precision@3": 0.36192915066154496,
-      "eval_dim_1024_cosine_precision@5": 0.35172855313700385,
-      "eval_dim_1024_cosine_recall@1": 0.04346309464734114,
-      "eval_dim_1024_cosine_recall@10": 0.28096984500258326,
-      "eval_dim_1024_cosine_recall@3": 0.12757812796185336,
-      "eval_dim_1024_cosine_recall@5": 0.19200836801442767,
-      "eval_dim_128_cosine_accuracy@1": 0.3085787451984635,
-      "eval_dim_128_cosine_accuracy@10": 0.37964148527528807,
-      "eval_dim_128_cosine_accuracy@3": 0.31241997439180536,
       "eval_dim_128_cosine_accuracy@5": 0.3361075544174136,
-      "eval_dim_128_cosine_map@100": 0.3963095303049961,
-      "eval_dim_128_cosine_mrr@10": 0.3199812511432227,
-      "eval_dim_128_cosine_ndcg@10": 0.3312285498294292,
-      "eval_dim_128_cosine_precision@1": 0.3085787451984635,
-      "eval_dim_128_cosine_precision@10": 0.2752880921895006,
-      "eval_dim_128_cosine_precision@3": 0.3079385403329065,
-      "eval_dim_128_cosine_precision@5": 0.29961587708066584,
-      "eval_dim_128_cosine_recall@1": 0.036297623853982414,
-      "eval_dim_128_cosine_recall@10": 0.24000960695821508,
-      "eval_dim_128_cosine_recall@3": 0.10638786483158841,
-      "eval_dim_128_cosine_recall@5": 0.16032639984514846,
-      "eval_dim_256_cosine_accuracy@1": 0.3437900128040973,
-      "eval_dim_256_cosine_accuracy@10": 0.41101152368758004,
-      "eval_dim_256_cosine_accuracy@3": 0.34763124199743917,
-      "eval_dim_256_cosine_accuracy@5": 0.3764404609475032,
-      "eval_dim_256_cosine_map@100": 0.4298669852983799,
-      "eval_dim_256_cosine_mrr@10": 0.3551361197487955,
-      "eval_dim_256_cosine_ndcg@10": 0.3670052960875804,
-      "eval_dim_256_cosine_precision@1": 0.3437900128040973,
-      "eval_dim_256_cosine_precision@10": 0.3040973111395647,
-      "eval_dim_256_cosine_precision@3": 0.342936406316688,
-      "eval_dim_256_cosine_precision@5": 0.33457106274007686,
-      "eval_dim_256_cosine_recall@1": 0.04013102608834382,
-      "eval_dim_256_cosine_recall@10": 0.2648598688529433,
-      "eval_dim_256_cosine_recall@3": 0.11771735023719074,
-      "eval_dim_256_cosine_recall@5": 0.17837935755014916,
-      "eval_dim_512_cosine_accuracy@1": 0.35979513444302175,
-      "eval_dim_512_cosine_accuracy@10": 0.4334186939820743,
-      "eval_dim_512_cosine_accuracy@3": 0.36555697823303457,
-      "eval_dim_512_cosine_accuracy@5": 0.3911651728553137,
-      "eval_dim_512_cosine_map@100": 0.4476805587612892,
-      "eval_dim_512_cosine_mrr@10": 0.37212542934373866,
-      "eval_dim_512_cosine_ndcg@10": 0.3843750966464458,
-      "eval_dim_512_cosine_precision@1": 0.35979513444302175,
-      "eval_dim_512_cosine_precision@10": 0.3173495518565941,
-      "eval_dim_512_cosine_precision@3": 0.35936833119931705,
-      "eval_dim_512_cosine_precision@5": 0.34967989756722156,
-      "eval_dim_512_cosine_recall@1": 0.04265405128130224,
-      "eval_dim_512_cosine_recall@10": 0.2781876565001863,
-      "eval_dim_512_cosine_recall@3": 0.12523102347193127,
-      "eval_dim_512_cosine_recall@5": 0.18912519336740205,
-      "eval_dim_64_cosine_accuracy@1": 0.2740076824583867,
-      "eval_dim_64_cosine_accuracy@10": 0.3354673495518566,
-      "eval_dim_64_cosine_accuracy@3": 0.27848911651728553,
-      "eval_dim_64_cosine_accuracy@5": 0.30153649167733676,
-      "eval_dim_64_cosine_map@100": 0.3539045084602349,
-      "eval_dim_64_cosine_mrr@10": 0.28429414873076814,
-      "eval_dim_64_cosine_ndcg@10": 0.29402896525927075,
-      "eval_dim_64_cosine_precision@1": 0.2740076824583867,
-      "eval_dim_64_cosine_precision@10": 0.24571062740076827,
-      "eval_dim_64_cosine_precision@3": 0.27315407597097735,
-      "eval_dim_64_cosine_precision@5": 0.2670934699103713,
-      "eval_dim_64_cosine_recall@1": 0.03167890172057568,
-      "eval_dim_64_cosine_recall@10": 0.21092883720941633,
-      "eval_dim_64_cosine_recall@3": 0.09267023360511464,
-      "eval_dim_64_cosine_recall@5": 0.14048625468314752,
-      "eval_dim_768_cosine_accuracy@1": 0.3591549295774648,
-      "eval_dim_768_cosine_accuracy@10": 0.4334186939820743,
-      "eval_dim_768_cosine_accuracy@3": 0.3649167733674776,
-      "eval_dim_768_cosine_accuracy@5": 0.3892445582586428,
-      "eval_dim_768_cosine_map@100": 0.4493001842217619,
-      "eval_dim_768_cosine_mrr@10": 0.37149335406377615,
-      "eval_dim_768_cosine_ndcg@10": 0.38308181752122755,
-      "eval_dim_768_cosine_precision@1": 0.3591549295774648,
-      "eval_dim_768_cosine_precision@10": 0.31670934699103714,
-      "eval_dim_768_cosine_precision@3": 0.3587281263337601,
-      "eval_dim_768_cosine_precision@5": 0.34852752880921894,
-      "eval_dim_768_cosine_recall@1": 0.04250079684114586,
-      "eval_dim_768_cosine_recall@10": 0.27695909667507057,
-      "eval_dim_768_cosine_recall@3": 0.12462187901616553,
-      "eval_dim_768_cosine_recall@5": 0.1875478484365334,
-      "eval_runtime": 99.0843,
       "eval_samples_per_second": 0.0,
-      "eval_sequential_score": 0.29402896525927075,
       "eval_steps_per_second": 0.0,
       "step": 98
     }

 {
   "best_global_step": 98,
+  "best_metric": 0.3299991425713933,
   "best_model_checkpoint": "intfloat/multilingual-e5-large/checkpoint-98",
   "epoch": 1.0,
   "eval_steps": 500,
   "log_history": [
     {
       "epoch": 0.01020408163265306,
+      "grad_norm": 196.63563537597656,
       "learning_rate": 0.0,
+      "loss": 4.0658,
       "step": 1
     },
     {
       "epoch": 0.02040816326530612,
+      "grad_norm": 184.93710327148438,
       "learning_rate": 1.0204081632653061e-07,
+      "loss": 5.2785,
       "step": 2
     },
     {
       "epoch": 0.030612244897959183,
+      "grad_norm": 179.60655212402344,
       "learning_rate": 2.0408163265306121e-07,
+      "loss": 4.349,
       "step": 3
     },
     {
       "epoch": 0.04081632653061224,
+      "grad_norm": 163.9447479248047,
       "learning_rate": 3.0612244897959183e-07,
+      "loss": 3.805,
       "step": 4
     },
     {
       "epoch": 0.05102040816326531,
+      "grad_norm": 164.29776000976562,
       "learning_rate": 4.0816326530612243e-07,
+      "loss": 3.1683,
       "step": 5
     },
     {
       "epoch": 0.061224489795918366,
+      "grad_norm": 209.0354766845703,
       "learning_rate": 5.102040816326531e-07,
+      "loss": 5.3989,
       "step": 6
     },
     {
       "epoch": 0.07142857142857142,
+      "grad_norm": 262.14971923828125,
       "learning_rate": 6.122448979591837e-07,
+      "loss": 8.211,
       "step": 7
     },
     {
       "epoch": 0.08163265306122448,
+      "grad_norm": 188.68443298339844,
       "learning_rate": 7.142857142857143e-07,
+      "loss": 5.3598,
       "step": 8
     },
     {
       "epoch": 0.09183673469387756,
+      "grad_norm": 216.530517578125,
       "learning_rate": 8.163265306122449e-07,
+      "loss": 5.0522,
       "step": 9
     },
     {
       "epoch": 0.10204081632653061,
+      "grad_norm": 231.66384887695312,
       "learning_rate": 9.183673469387756e-07,
+      "loss": 4.4736,
       "step": 10
     },
     {
       "epoch": 0.11224489795918367,
+      "grad_norm": 329.2440490722656,
       "learning_rate": 1.0204081632653063e-06,
+      "loss": 8.3251,
       "step": 11
     },
     {
       "epoch": 0.12244897959183673,
+      "grad_norm": 102.95913696289062,
       "learning_rate": 1.122448979591837e-06,
+      "loss": 2.5822,
       "step": 12
     },
     {
       "epoch": 0.1326530612244898,
+      "grad_norm": 116.47322845458984,
       "learning_rate": 1.2244897959183673e-06,
+      "loss": 2.8464,
       "step": 13
     },
     {
       "epoch": 0.14285714285714285,
+      "grad_norm": 226.98976135253906,
       "learning_rate": 1.3265306122448982e-06,
+      "loss": 5.8915,
       "step": 14
     },
     {
       "epoch": 0.15306122448979592,
+      "grad_norm": 192.4533233642578,
       "learning_rate": 1.4285714285714286e-06,
+      "loss": 7.2637,
       "step": 15
     },
     {
       "epoch": 0.16326530612244897,
+      "grad_norm": 269.7630920410156,
       "learning_rate": 1.5306122448979593e-06,
+      "loss": 7.4234,
       "step": 16
     },
     {
       "epoch": 0.17346938775510204,
+      "grad_norm": 111.28227233886719,
       "learning_rate": 1.6326530612244897e-06,
+      "loss": 2.3787,
       "step": 17
     },
     {
       "epoch": 0.1836734693877551,
+      "grad_norm": 165.55792236328125,
       "learning_rate": 1.7346938775510206e-06,
+      "loss": 3.1947,
       "step": 18
     },
     {
       "epoch": 0.19387755102040816,
+      "grad_norm": 152.33682250976562,
       "learning_rate": 1.8367346938775512e-06,
+      "loss": 3.4787,
       "step": 19
     },
     {
       "epoch": 0.20408163265306123,
+      "grad_norm": 159.368408203125,
       "learning_rate": 1.938775510204082e-06,
+      "loss": 5.1418,
       "step": 20
     },
     {
       "epoch": 0.21428571428571427,
+      "grad_norm": 112.97805786132812,
       "learning_rate": 2.0408163265306125e-06,
+      "loss": 2.3042,
       "step": 21
     },
     {
       "epoch": 0.22448979591836735,
+      "grad_norm": 199.43443298339844,
       "learning_rate": 2.1428571428571427e-06,
+      "loss": 6.6786,
       "step": 22
     },
     {
       "epoch": 0.23469387755102042,
+      "grad_norm": 241.95591735839844,
       "learning_rate": 2.244897959183674e-06,
+      "loss": 6.6721,
       "step": 23
     },
     {
       "epoch": 0.24489795918367346,
+      "grad_norm": 249.65122985839844,
       "learning_rate": 2.3469387755102044e-06,
+      "loss": 4.4896,
       "step": 24
     },
     {
       "epoch": 0.25510204081632654,
+      "grad_norm": 183.51483154296875,
       "learning_rate": 2.4489795918367347e-06,
+      "loss": 3.4416,
       "step": 25
     },
     {
       "epoch": 0.2653061224489796,
+      "grad_norm": 286.1512756347656,
       "learning_rate": 2.5510204081632657e-06,
+      "loss": 7.5134,
       "step": 26
     },
     {
       "epoch": 0.2755102040816326,
+      "grad_norm": 98.32283782958984,
       "learning_rate": 2.6530612244897964e-06,
+      "loss": 1.9577,
       "step": 27
     },
     {
       "epoch": 0.2857142857142857,
+      "grad_norm": 274.64178466796875,
       "learning_rate": 2.7551020408163266e-06,
+      "loss": 4.9552,
       "step": 28
     },
     {
       "epoch": 0.29591836734693877,
+      "grad_norm": 142.77537536621094,
       "learning_rate": 2.8571428571428573e-06,
+      "loss": 2.5202,
       "step": 29
     },
     {
       "epoch": 0.30612244897959184,
+      "grad_norm": 127.23304748535156,
       "learning_rate": 2.959183673469388e-06,
+      "loss": 2.4486,
       "step": 30
     },
     {
       "epoch": 0.3163265306122449,
+      "grad_norm": 99.88568878173828,
       "learning_rate": 3.0612244897959185e-06,
+      "loss": 1.9923,
       "step": 31
     },
     {
       "epoch": 0.32653061224489793,
+      "grad_norm": 151.1445770263672,
       "learning_rate": 3.1632653061224496e-06,
+      "loss": 2.8301,
       "step": 32
     },
     {
       "epoch": 0.336734693877551,
+      "grad_norm": 203.54248046875,
       "learning_rate": 3.2653061224489794e-06,
+      "loss": 3.7414,
       "step": 33
     },
     {
       "epoch": 0.3469387755102041,
+      "grad_norm": 443.4117126464844,
       "learning_rate": 3.3673469387755105e-06,
+      "loss": 5.2738,
       "step": 34
     },
     {
       "epoch": 0.35714285714285715,
+      "grad_norm": 178.9974822998047,
       "learning_rate": 3.469387755102041e-06,
+      "loss": 3.791,
       "step": 35
     },
     {
       "epoch": 0.3673469387755102,
+      "grad_norm": 122.32801818847656,
       "learning_rate": 3.5714285714285718e-06,
+      "loss": 1.9081,
       "step": 36
     },
     {
       "epoch": 0.37755102040816324,
+      "grad_norm": 189.6477813720703,
       "learning_rate": 3.6734693877551024e-06,
+      "loss": 2.4172,
       "step": 37
     },
     {
       "epoch": 0.3877551020408163,
+      "grad_norm": 222.67959594726562,
       "learning_rate": 3.7755102040816327e-06,
+      "loss": 4.0417,
       "step": 38
     },
     {
       "epoch": 0.3979591836734694,
+      "grad_norm": 160.97071838378906,
       "learning_rate": 3.877551020408164e-06,
+      "loss": 3.5591,
       "step": 39
     },
     {
       "epoch": 0.40816326530612246,
+      "grad_norm": 178.01609802246094,
       "learning_rate": 3.979591836734694e-06,
+      "loss": 3.0139,
       "step": 40
     },
     {
       "epoch": 0.41836734693877553,
+      "grad_norm": 142.32168579101562,
       "learning_rate": 4.081632653061225e-06,
+      "loss": 2.4836,
       "step": 41
     },
     {
       "epoch": 0.42857142857142855,
+      "grad_norm": 148.1731719970703,
       "learning_rate": 4.183673469387755e-06,
+      "loss": 2.807,
       "step": 42
     },
     {
       "epoch": 0.4387755102040816,
+      "grad_norm": 152.1929931640625,
       "learning_rate": 4.2857142857142855e-06,
+      "loss": 1.9753,
       "step": 43
     },
     {
       "epoch": 0.4489795918367347,
+      "grad_norm": 219.5394287109375,
       "learning_rate": 4.3877551020408165e-06,
+      "loss": 0.9764,
       "step": 44
     },
     {
       "epoch": 0.45918367346938777,
+      "grad_norm": 95.7768783569336,
       "learning_rate": 4.489795918367348e-06,
+      "loss": 1.1398,
       "step": 45
     },
     {
       "epoch": 0.46938775510204084,
+      "grad_norm": 320.86529541015625,
       "learning_rate": 4.591836734693878e-06,
+      "loss": 6.7812,
       "step": 46
     },
     {
       "epoch": 0.47959183673469385,
+      "grad_norm": 18.277860641479492,
       "learning_rate": 4.693877551020409e-06,
+      "loss": 0.2479,
       "step": 47
     },
     {
       "epoch": 0.4897959183673469,
+      "grad_norm": 405.69024658203125,
       "learning_rate": 4.795918367346939e-06,
+      "loss": 6.041,
       "step": 48
     },
     {
       "epoch": 0.5,
+      "grad_norm": 104.91180419921875,
       "learning_rate": 4.897959183673469e-06,
+      "loss": 1.1839,
       "step": 49
     },
     {
       "epoch": 0.5102040816326531,
+      "grad_norm": 110.48990631103516,
       "learning_rate": 5e-06,
+      "loss": 2.0933,
       "step": 50
     },
     {
       "epoch": 0.5204081632653061,
+      "grad_norm": 135.2900390625,
       "learning_rate": 5.1020408163265315e-06,
+      "loss": 1.8613,
       "step": 51
     },
     {
       "epoch": 0.5306122448979592,
+      "grad_norm": 146.744140625,
       "learning_rate": 5.204081632653062e-06,
+      "loss": 2.9359,
       "step": 52
     },
     {
       "epoch": 0.5408163265306123,
+      "grad_norm": 103.08831787109375,
       "learning_rate": 5.306122448979593e-06,
+      "loss": 1.0129,
       "step": 53
     },
     {
       "epoch": 0.5510204081632653,
+      "grad_norm": 527.3735961914062,
       "learning_rate": 5.408163265306123e-06,
+      "loss": 11.8843,
       "step": 54
     },
     {
       "epoch": 0.5612244897959183,
+      "grad_norm": 374.4621887207031,
       "learning_rate": 5.510204081632653e-06,
+      "loss": 5.8523,
       "step": 55
     },
     {
       "epoch": 0.5714285714285714,
+      "grad_norm": 71.62016296386719,
       "learning_rate": 5.6122448979591834e-06,
+      "loss": 0.832,
       "step": 56
     },
     {
       "epoch": 0.5816326530612245,
+      "grad_norm": 287.0186462402344,
       "learning_rate": 5.7142857142857145e-06,
+      "loss": 3.1778,
       "step": 57
     },
     {
       "epoch": 0.5918367346938775,
+      "grad_norm": 31.022693634033203,
       "learning_rate": 5.816326530612246e-06,
+      "loss": 0.3919,
       "step": 58
     },
     {
       "epoch": 0.6020408163265306,
+      "grad_norm": 412.99176025390625,
       "learning_rate": 5.918367346938776e-06,
+      "loss": 7.2526,
       "step": 59
     },
     {
       "epoch": 0.6122448979591837,
+      "grad_norm": 40.534244537353516,
       "learning_rate": 6.020408163265307e-06,
+      "loss": 0.578,
       "step": 60
     },
     {
       "epoch": 0.6224489795918368,
+      "grad_norm": 226.0243682861328,
       "learning_rate": 6.122448979591837e-06,
+      "loss": 2.5233,
       "step": 61
     },
     {
       "epoch": 0.6326530612244898,
+      "grad_norm": 113.55558013916016,
       "learning_rate": 6.224489795918368e-06,
+      "loss": 1.5694,
       "step": 62
     },
     {
       "epoch": 0.6428571428571429,
+      "grad_norm": 190.6112518310547,
       "learning_rate": 6.326530612244899e-06,
+      "loss": 2.2332,
       "step": 63
     },
     {
       "epoch": 0.6530612244897959,
+      "grad_norm": 391.7434387207031,
       "learning_rate": 6.4285714285714295e-06,
+      "loss": 4.5545,
       "step": 64
     },
     {
       "epoch": 0.6632653061224489,
+      "grad_norm": 214.495361328125,
       "learning_rate": 6.530612244897959e-06,
+      "loss": 1.4804,
       "step": 65
     },
     {
       "epoch": 0.673469387755102,
+      "grad_norm": 62.52560806274414,
       "learning_rate": 6.63265306122449e-06,
+      "loss": 0.4391,
       "step": 66
     },
     {
       "epoch": 0.6836734693877551,
+      "grad_norm": 298.97808837890625,
       "learning_rate": 6.734693877551021e-06,
+      "loss": 3.4715,
       "step": 67
     },
     {
       "epoch": 0.6938775510204082,
+      "grad_norm": 483.84796142578125,
       "learning_rate": 6.836734693877551e-06,
+      "loss": 8.5808,
       "step": 68
     },
     {
       "epoch": 0.7040816326530612,
+      "grad_norm": 482.55743408203125,
       "learning_rate": 6.938775510204082e-06,
+      "loss": 5.6959,
       "step": 69
     },
     {
       "epoch": 0.7142857142857143,
+      "grad_norm": 198.6812744140625,
       "learning_rate": 7.0408163265306125e-06,
+      "loss": 3.8277,
       "step": 70
     },
     {
       "epoch": 0.7244897959183674,
+      "grad_norm": 293.4190673828125,
       "learning_rate": 7.1428571428571436e-06,
+      "loss": 2.1832,
       "step": 71
     },
     {
       "epoch": 0.7346938775510204,
+      "grad_norm": 13.164139747619629,
       "learning_rate": 7.244897959183675e-06,
+      "loss": 0.1244,
       "step": 72
     },
     {
       "epoch": 0.7448979591836735,
+      "grad_norm": 163.4252166748047,
       "learning_rate": 7.346938775510205e-06,
+      "loss": 0.7707,
       "step": 73
     },
     {
       "epoch": 0.7551020408163265,
+      "grad_norm": 193.64401245117188,
       "learning_rate": 7.448979591836736e-06,
+      "loss": 3.4828,
       "step": 74
     },
     {
       "epoch": 0.7653061224489796,
+      "grad_norm": 178.31982421875,
       "learning_rate": 7.551020408163265e-06,
+      "loss": 2.9645,
       "step": 75
     },
     {
       "epoch": 0.7755102040816326,
+      "grad_norm": 28.57689666748047,
       "learning_rate": 7.653061224489796e-06,
+      "loss": 0.2948,
       "step": 76
     },
     {
       "epoch": 0.7857142857142857,
+      "grad_norm": 608.8088989257812,
       "learning_rate": 7.755102040816327e-06,
+      "loss": 12.6456,
       "step": 77
     },
     {
       "epoch": 0.7959183673469388,
+      "grad_norm": 123.08556365966797,
       "learning_rate": 7.857142857142858e-06,
+      "loss": 1.2493,
       "step": 78
     },
     {
       "epoch": 0.8061224489795918,
+      "grad_norm": 225.3292694091797,
       "learning_rate": 7.959183673469388e-06,
+      "loss": 2.6675,
       "step": 79
     },
     {
       "epoch": 0.8163265306122449,
+      "grad_norm": 57.49665069580078,
       "learning_rate": 8.06122448979592e-06,
+      "loss": 0.5642,
       "step": 80
     },
     {
       "epoch": 0.826530612244898,
+      "grad_norm": 247.52210998535156,
       "learning_rate": 8.16326530612245e-06,
+      "loss": 1.6008,
       "step": 81
     },
     {
       "epoch": 0.8367346938775511,
+      "grad_norm": 309.60382080078125,
       "learning_rate": 8.26530612244898e-06,
+      "loss": 3.257,
       "step": 82
     },
     {
       "epoch": 0.8469387755102041,
+      "grad_norm": 183.82882690429688,
       "learning_rate": 8.36734693877551e-06,
+      "loss": 2.8086,
       "step": 83
     },
     {
       "epoch": 0.8571428571428571,
+      "grad_norm": 88.08740234375,
       "learning_rate": 8.469387755102042e-06,
+      "loss": 0.4056,
       "step": 84
     },
     {
       "epoch": 0.8673469387755102,
+      "grad_norm": 515.5130615234375,
       "learning_rate": 8.571428571428571e-06,
+      "loss": 3.711,
       "step": 85
     },
     {
       "epoch": 0.8775510204081632,
+      "grad_norm": 2.946629285812378,
       "learning_rate": 8.673469387755103e-06,
+      "loss": 0.0253,
       "step": 86
     },
     {
       "epoch": 0.8877551020408163,
+      "grad_norm": 31.143714904785156,
       "learning_rate": 8.775510204081633e-06,
+      "loss": 0.168,
       "step": 87
     },
     {
       "epoch": 0.8979591836734694,
+      "grad_norm": 535.6795043945312,
       "learning_rate": 8.877551020408163e-06,
+      "loss": 5.0992,
       "step": 88
     },
     {
       "epoch": 0.9081632653061225,
+      "grad_norm": 577.0897216796875,
       "learning_rate": 8.979591836734695e-06,
+      "loss": 5.3724,
       "step": 89
     },
     {
       "epoch": 0.9183673469387755,
+      "grad_norm": 102.31855773925781,
       "learning_rate": 9.081632653061225e-06,
+      "loss": 0.9172,
       "step": 90
     },
     {
       "epoch": 0.9285714285714286,
+      "grad_norm": 306.1739196777344,
       "learning_rate": 9.183673469387756e-06,
+      "loss": 3.1239,
       "step": 91
     },
     {
       "epoch": 0.9387755102040817,
+      "grad_norm": 191.27415466308594,
       "learning_rate": 9.285714285714288e-06,
+      "loss": 1.4121,
       "step": 92
     },
     {
       "epoch": 0.9489795918367347,
+      "grad_norm": 67.19822692871094,
       "learning_rate": 9.387755102040818e-06,
+      "loss": 0.2599,
       "step": 93
     },
     {
       "epoch": 0.9591836734693877,
+      "grad_norm": 17.93955421447754,
       "learning_rate": 9.489795918367348e-06,
+      "loss": 0.1166,
       "step": 94
     },
     {
       "epoch": 0.9693877551020408,
+      "grad_norm": 23.839630126953125,
       "learning_rate": 9.591836734693878e-06,
+      "loss": 0.1938,
       "step": 95
     },
     {
       "epoch": 0.9795918367346939,
+      "grad_norm": 1459.8140869140625,
       "learning_rate": 9.693877551020408e-06,
+      "loss": 18.5143,
       "step": 96
     },
     {
       "epoch": 0.9897959183673469,
+      "grad_norm": 670.869140625,
       "learning_rate": 9.795918367346939e-06,
+      "loss": 6.1932,
       "step": 97
     },
     {
       "epoch": 1.0,
+      "grad_norm": 942.95849609375,
       "learning_rate": 9.89795918367347e-06,
+      "loss": 20.3042,
       "step": 98
     },
     {
       "epoch": 1.0,
+      "eval_dim_1024_cosine_accuracy@1": 0.3719590268886043,
+      "eval_dim_1024_cosine_accuracy@10": 0.43982074263764404,
+      "eval_dim_1024_cosine_accuracy@3": 0.37836107554417414,
+      "eval_dim_1024_cosine_accuracy@5": 0.4020486555697823,
+      "eval_dim_1024_cosine_map@100": 0.4604070214987707,
+      "eval_dim_1024_cosine_mrr@10": 0.383397099770339,
+      "eval_dim_1024_cosine_ndcg@10": 0.3947688545057553,
+      "eval_dim_1024_cosine_precision@1": 0.3719590268886043,
+      "eval_dim_1024_cosine_precision@10": 0.3265044814340589,
+      "eval_dim_1024_cosine_precision@3": 0.37153222364489963,
+      "eval_dim_1024_cosine_precision@5": 0.3613316261203585,
+      "eval_dim_1024_cosine_recall@1": 0.04338670134208909,
+      "eval_dim_1024_cosine_recall@10": 0.28262195979320087,
+      "eval_dim_1024_cosine_recall@3": 0.1268773565773867,
+      "eval_dim_1024_cosine_recall@5": 0.19083511167371434,
+      "eval_dim_128_cosine_accuracy@1": 0.3053777208706786,
+      "eval_dim_128_cosine_accuracy@10": 0.37836107554417414,
+      "eval_dim_128_cosine_accuracy@3": 0.3111395646606914,
       "eval_dim_128_cosine_accuracy@5": 0.3361075544174136,
+      "eval_dim_128_cosine_map@100": 0.3904168259576031,
+      "eval_dim_128_cosine_mrr@10": 0.3174377070503828,
+      "eval_dim_128_cosine_ndcg@10": 0.3299991425713933,
+      "eval_dim_128_cosine_precision@1": 0.3053777208706786,
+      "eval_dim_128_cosine_precision@10": 0.271830985915493,
+      "eval_dim_128_cosine_precision@3": 0.30495091762697396,
+      "eval_dim_128_cosine_precision@5": 0.29641485275288093,
+      "eval_dim_128_cosine_recall@1": 0.03688049871840266,
+      "eval_dim_128_cosine_recall@10": 0.24260019246216608,
+      "eval_dim_128_cosine_recall@3": 0.10779952005618963,
+      "eval_dim_128_cosine_recall@5": 0.16176912684922656,
+      "eval_dim_256_cosine_accuracy@1": 0.324583866837388,
+      "eval_dim_256_cosine_accuracy@10": 0.4058898847631242,
+      "eval_dim_256_cosine_accuracy@3": 0.33290653008962867,
+      "eval_dim_256_cosine_accuracy@5": 0.3649167733674776,
+      "eval_dim_256_cosine_map@100": 0.4232469199200366,
+      "eval_dim_256_cosine_mrr@10": 0.33872299453285326,
+      "eval_dim_256_cosine_ndcg@10": 0.35307499975694673,
+      "eval_dim_256_cosine_precision@1": 0.324583866837388,
+      "eval_dim_256_cosine_precision@10": 0.2935339308578745,
+      "eval_dim_256_cosine_precision@3": 0.324583866837388,
+      "eval_dim_256_cosine_precision@5": 0.31792573623559534,
+      "eval_dim_256_cosine_recall@1": 0.038313787861467184,
+      "eval_dim_256_cosine_recall@10": 0.2549878568107636,
+      "eval_dim_256_cosine_recall@3": 0.11223891931505588,
+      "eval_dim_256_cosine_recall@5": 0.1697408782100328,
+      "eval_dim_512_cosine_accuracy@1": 0.34827144686299616,
+      "eval_dim_512_cosine_accuracy@10": 0.44302176696542894,
+      "eval_dim_512_cosine_accuracy@3": 0.3553137003841229,
+      "eval_dim_512_cosine_accuracy@5": 0.39436619718309857,
+      "eval_dim_512_cosine_map@100": 0.44994622162234726,
+      "eval_dim_512_cosine_mrr@10": 0.3644033392272826,
+      "eval_dim_512_cosine_ndcg@10": 0.3807642678190648,
+      "eval_dim_512_cosine_precision@1": 0.34827144686299616,
+      "eval_dim_512_cosine_precision@10": 0.31798975672215113,
+      "eval_dim_512_cosine_precision@3": 0.34827144686299616,
+      "eval_dim_512_cosine_precision@5": 0.3418693982074264,
+      "eval_dim_512_cosine_recall@1": 0.04125738861359979,
+      "eval_dim_512_cosine_recall@10": 0.2752162089385945,
+      "eval_dim_512_cosine_recall@3": 0.12077279112247459,
+      "eval_dim_512_cosine_recall@5": 0.18268801127884626,
+      "eval_dim_64_cosine_accuracy@1": 0.23175416133162613,
+      "eval_dim_64_cosine_accuracy@10": 0.29833546734955185,
+      "eval_dim_64_cosine_accuracy@3": 0.23879641485275288,
+      "eval_dim_64_cosine_accuracy@5": 0.2612035851472471,
+      "eval_dim_64_cosine_map@100": 0.3151829220617657,
+      "eval_dim_64_cosine_mrr@10": 0.24303802613661746,
+      "eval_dim_64_cosine_ndcg@10": 0.2548721998123125,
+      "eval_dim_64_cosine_precision@1": 0.23175416133162613,
+      "eval_dim_64_cosine_precision@10": 0.20864276568501922,
+      "eval_dim_64_cosine_precision@3": 0.23218096457533077,
+      "eval_dim_64_cosine_precision@5": 0.22740076824583869,
+      "eval_dim_64_cosine_recall@1": 0.028384798943475897,
+      "eval_dim_64_cosine_recall@10": 0.19540887275051927,
+      "eval_dim_64_cosine_recall@3": 0.08325514613360847,
+      "eval_dim_64_cosine_recall@5": 0.12720688223912358,
+      "eval_dim_768_cosine_accuracy@1": 0.36619718309859156,
+      "eval_dim_768_cosine_accuracy@10": 0.44302176696542894,
+      "eval_dim_768_cosine_accuracy@3": 0.37516005121638923,
+      "eval_dim_768_cosine_accuracy@5": 0.4014084507042254,
+      "eval_dim_768_cosine_map@100": 0.4592162636155952,
+      "eval_dim_768_cosine_mrr@10": 0.37943672133812956,
+      "eval_dim_768_cosine_ndcg@10": 0.3923099208699586,
+      "eval_dim_768_cosine_precision@1": 0.36619718309859156,
+      "eval_dim_768_cosine_precision@10": 0.32541613316261203,
+      "eval_dim_768_cosine_precision@3": 0.3666239863422962,
+      "eval_dim_768_cosine_precision@5": 0.35761843790012804,
+      "eval_dim_768_cosine_recall@1": 0.042908107176418055,
+      "eval_dim_768_cosine_recall@10": 0.2828362934197418,
+      "eval_dim_768_cosine_recall@3": 0.12573828441229515,
+      "eval_dim_768_cosine_recall@5": 0.18984022934199501,
+      "eval_runtime": 98.8905,
       "eval_samples_per_second": 0.0,
+      "eval_sequential_score": 0.2548721998123125,
       "eval_steps_per_second": 0.0,
       "step": 98
     }

checkpoint-98/training_args.bin CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:739b4a0a62fdf782034d2ababe5e5ea588023ed6263f2604e31385fc77a8faab
 size 6097

 version https://git-lfs.github.com/spec/v1
+oid sha256:8a0318feaae2d8aeaebeec5835b4bc77eb79a026385dfb908828064d2f4fd294
 size 6097

eval/Information-Retrieval_evaluation_dim_1024_results.csv CHANGED Viewed

@@ -1,7 +1,4 @@
 epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
-1.0,98,0.3758002560819462,0.38092189500640206,0.42189500640204863,0.46350832266325226,0.3758002560819462,0.04194926351085856,0.3758002560819462,0.12414468143510038,0.3700384122919334,0.19046123021012357,0.3443661971830986,0.2917779043677444,0.390878350913562,0.40707429228028374,0.470393135872763
-2.0,196,0.323943661971831,0.3348271446862996,0.3725992317541613,0.41165172855313703,0.323943661971831,0.03729875848331919,0.32565087494664957,0.11010828228304573,0.32215108834827144,0.1691095157664461,0.30121638924455824,0.25941286480210374,0.3400178850883073,0.35730245744576905,0.42245999663664574
-3.0,294,0.30217669654289375,0.3111395646606914,0.3444302176696543,0.382842509603073,0.30217669654289375,0.03408811614897108,0.3034571062740077,0.1010394072515041,0.2997439180537772,0.15530224859949704,0.2768886043533931,0.23384842264767727,0.31628610044102934,0.33035731141222535,0.39467218596398806
-1.0,98,0.36235595390524966,0.3681177976952625,0.39308578745198464,0.4334186939820743,0.36235595390524966,0.04346309464734114,0.36192915066154496,0.12757812796185336,0.35172855313700385,0.19200836801442767,0.3176696542893726,0.28096984500258326,0.37430415828303115,0.3858809020056271,0.45394800707643057
-2.0,196,0.32522407170294493,0.33290653008962867,0.36043533930857874,0.3969270166453265,0.32522407170294493,0.04113491331982186,0.3254374733247973,0.12080229545561262,0.31626120358514725,0.18183789253196145,0.28361075544174136,0.2664549051060991,0.33769460195516493,0.34986350069216465,0.4164888021641558
-3.0,294,0.30985915492957744,0.31498079385403327,0.34699103713188223,0.37836107554417414,0.30985915492957744,0.03936027574360421,0.30900554844216815,0.11544349976954149,0.30115236875800255,0.17456487753074904,0.2694622279129321,0.2548212686119806,0.32174181452350414,0.33364818903542787,0.3968421394024028

 epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
+1.0,98,0.3719590268886043,0.37836107554417414,0.4020486555697823,0.43982074263764404,0.3719590268886043,0.04338670134208909,0.37153222364489963,0.1268773565773867,0.3613316261203585,0.19083511167371434,0.3265044814340589,0.28262195979320087,0.383397099770339,0.3947688545057553,0.4604070214987707
+2.0,196,0.3591549295774648,0.3649167733674776,0.39308578745198464,0.42445582586427655,0.3591549295774648,0.040925664980934,0.35830132309005547,0.11912044022990924,0.3495518565941101,0.17907504115268522,0.31914212548015364,0.2663878590041381,0.37061688311688284,0.38277564232489586,0.4442656203645836
+3.0,294,0.3354673495518566,0.3405889884763124,0.3725992317541613,0.41357234314980795,0.3354673495518566,0.0398374526951408,0.33418693982074266,0.11613369449549121,0.3261203585147247,0.1745427554610417,0.2996798975672215,0.26082122731297214,0.34860069507956787,0.3620561774122382,0.4292335776181432

eval/Information-Retrieval_evaluation_dim_128_results.csv CHANGED Viewed

@@ -1,7 +1,4 @@
 epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
-1.0,98,0.3034571062740077,0.31049935979513443,0.3418693982074264,0.38092189500640206,0.3034571062740077,0.033684401658902394,0.3038839095177123,0.0993687488012139,0.2994878361075545,0.1530597677971524,0.27951344430217673,0.23623301896460966,0.31698549885169575,0.3316022948596431,0.3880699945060264
-2.0,196,0.26312419974391804,0.27208706786171577,0.3040973111395647,0.3437900128040973,0.26312419974391804,0.030292339319323316,0.264404609475032,0.08932760883813833,0.2622279129321383,0.13813514940643304,0.24705505761843788,0.21401864973389503,0.27745640509724984,0.2925461220092893,0.35443528477119834
-3.0,294,0.2528809218950064,0.2573623559539053,0.2855313700384123,0.31562099871959026,0.2528809218950064,0.026569332449478945,0.2528809218950064,0.07825317283023206,0.24942381562099875,0.11986554677533047,0.23405889884763126,0.18209399283843894,0.26369479503282284,0.274763189652588,0.32691762851003603
-1.0,98,0.3085787451984635,0.31241997439180536,0.3361075544174136,0.37964148527528807,0.3085787451984635,0.036297623853982414,0.3079385403329065,0.10638786483158841,0.29961587708066584,0.16032639984514846,0.2752880921895006,0.24000960695821508,0.3199812511432227,0.3312285498294292,0.3963095303049961
-2.0,196,0.30217669654289375,0.3072983354673495,0.3265044814340589,0.3546734955185659,0.30217669654289375,0.03603846894598867,0.30239009816474605,0.10607255532328354,0.29359795134443023,0.15998840334482403,0.26312419974391804,0.23664446759855584,0.3112729406743488,0.32071443787836906,0.38014172959059034
-3.0,294,0.2765685019206146,0.2887323943661972,0.31882202304737517,0.3501920614596671,0.2765685019206146,0.03462627857091171,0.2787025181391378,0.10222485929387912,0.27413572343149806,0.15567435868523452,0.24916773367477596,0.23219859983003413,0.29051937889966023,0.3054184027921396,0.36208318391000843

 epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
+1.0,98,0.3053777208706786,0.3111395646606914,0.3361075544174136,0.37836107554417414,0.3053777208706786,0.03688049871840266,0.30495091762697396,0.10779952005618963,0.29641485275288093,0.16176912684922656,0.271830985915493,0.24260019246216608,0.3174377070503828,0.3299991425713933,0.3904168259576031
+2.0,196,0.3060179257362356,0.31049935979513443,0.3322663252240717,0.3687580025608195,0.3060179257362356,0.035453426807775947,0.3053777208706786,0.10361683841932247,0.29679897567221514,0.15549008066651587,0.27099871959026883,0.23154232181544257,0.3164926427250368,0.3273120368593549,0.38523839229741214
+3.0,294,0.2874519846350832,0.2919334186939821,0.3207426376440461,0.36299615877080665,0.2874519846350832,0.03347207506231567,0.28638497652582157,0.09769125063098655,0.2796414852752881,0.14652568796520726,0.260179257362356,0.2200069729736681,0.29988542365302884,0.3121618176452898,0.37222007780985544

eval/Information-Retrieval_evaluation_dim_256_results.csv CHANGED Viewed

@@ -1,7 +1,4 @@
 epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
-1.0,98,0.3412291933418694,0.34635083226632524,0.38348271446862997,0.42573623559539053,0.3412291933418694,0.03848278551561358,0.34101579172001706,0.11327945737089931,0.3354673495518566,0.1731366734431563,0.31241997439180536,0.2637956260522792,0.35570315834400307,0.3711945274033381,0.43658178532295944
-2.0,196,0.2797695262483995,0.293854033290653,0.32842509603072984,0.37451984635083224,0.2797695262483995,0.032498552866695056,0.2825437473324798,0.09600029320659498,0.2809218950064021,0.1479519425167412,0.26677336747759284,0.23047217237905318,0.29707690587972235,0.31483989393569145,0.38160012953782213
-3.0,294,0.2740076824583867,0.28169014084507044,0.31562099871959026,0.34763124199743917,0.2740076824583867,0.02872973938731268,0.2750746905676483,0.08491580875997423,0.2736235595390525,0.13128424269244784,0.25832266325224074,0.2042482031495929,0.28722029144564304,0.30137677496002707,0.355446615033308
-1.0,98,0.3437900128040973,0.34763124199743917,0.3764404609475032,0.41101152368758004,0.3437900128040973,0.04013102608834382,0.342936406316688,0.11771735023719074,0.33457106274007686,0.17837935755014916,0.3040973111395647,0.2648598688529433,0.3551361197487955,0.3670052960875804,0.4298669852983799
-2.0,196,0.31049935979513443,0.31882202304737517,0.34571062740076824,0.3725992317541613,0.31049935979513443,0.0379038673811849,0.3109261630388391,0.11184662439829526,0.3035851472471191,0.16972372403865282,0.2727272727272727,0.25061548215235363,0.3219094872263883,0.33365785011470184,0.3940538127924734
-3.0,294,0.29577464788732394,0.3047375160051216,0.33098591549295775,0.3585147247119078,0.29577464788732394,0.03692836080135826,0.2968416559965856,0.1089192018057998,0.2898847631241997,0.16530160845995479,0.25845070422535216,0.24162273030445708,0.3073963985935813,0.31951819898251643,0.377358622211706

 epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
+1.0,98,0.324583866837388,0.33290653008962867,0.3649167733674776,0.4058898847631242,0.324583866837388,0.038313787861467184,0.324583866837388,0.11223891931505588,0.31792573623559534,0.1697408782100328,0.2935339308578745,0.2549878568107636,0.33872299453285326,0.35307499975694673,0.4232469199200366
+2.0,196,0.3290653008962868,0.33354673495518566,0.36235595390524966,0.3969270166453265,0.3290653008962868,0.03735817465789262,0.3282116944088775,0.10921822534273136,0.3209987195902689,0.165931214027115,0.29423815620998717,0.24868649598286982,0.3407241428368185,0.3532462927680357,0.4130430492367209
+3.0,294,0.3213828425096031,0.32842509603072984,0.3559539052496799,0.38988476312419973,0.3213828425096031,0.03683491421575636,0.32159624413145543,0.10829890857523781,0.31459667093469906,0.16421046118001698,0.28732394366197184,0.2447394908113676,0.3334143751397268,0.34585160474489407,0.40656810490109624

eval/Information-Retrieval_evaluation_dim_512_results.csv CHANGED Viewed

@@ -1,7 +1,4 @@
 epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
-1.0,98,0.354033290653009,0.36043533930857874,0.4033290653008963,0.4468629961587708,0.354033290653009,0.040213322698113355,0.3542466922748612,0.11849364024378686,0.349807938540333,0.181197723266763,0.32816901408450705,0.27659287824292283,0.3702490193687374,0.3875074092346156,0.4580788132793331
-2.0,196,0.29897567221510885,0.31306017925736235,0.34699103713188223,0.3879641485275288,0.29897567221510885,0.03524581966276957,0.3013230900554844,0.1041081313129689,0.29833546734955185,0.1595546072366398,0.27925736235595394,0.24463022936769843,0.31555926467898265,0.3326922254093368,0.39986627638770844
-3.0,294,0.2912932138284251,0.3002560819462228,0.32842509603072984,0.3706786171574904,0.2912932138284251,0.031548557747378574,0.2927870251813914,0.09357095555684627,0.2891165172855314,0.1435753152370639,0.26939820742637643,0.21891302574546295,0.3048952807755618,0.3179744532097737,0.3772797561888447
-1.0,98,0.35979513444302175,0.36555697823303457,0.3911651728553137,0.4334186939820743,0.35979513444302175,0.04265405128130224,0.35936833119931705,0.12523102347193127,0.34967989756722156,0.18912519336740205,0.3173495518565941,0.2781876565001863,0.37212542934373866,0.3843750966464458,0.4476805587612892
-2.0,196,0.32842509603072984,0.33418693982074266,0.36555697823303457,0.39564660691421255,0.32842509603072984,0.04071091183465321,0.3282116944088775,0.11970757850133786,0.31997439180537773,0.1806811237454132,0.28693982074263763,0.2638449444559509,0.34027168058858154,0.3525488928748249,0.4125328284000196
-3.0,294,0.3047375160051216,0.31049935979513443,0.34507042253521125,0.3719590268886043,0.3047375160051216,0.03902184942619328,0.30431071276141697,0.11440062517351587,0.29756722151088344,0.17317031567103489,0.2661331626120359,0.2526764166009778,0.31690623539215046,0.3300149893720946,0.39281877553256617

 epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
+1.0,98,0.34827144686299616,0.3553137003841229,0.39436619718309857,0.44302176696542894,0.34827144686299616,0.04125738861359979,0.34827144686299616,0.12077279112247459,0.3418693982074264,0.18268801127884626,0.31798975672215113,0.2752162089385945,0.3644033392272826,0.3807642678190648,0.44994622162234726
+2.0,196,0.3578745198463508,0.36299615877080665,0.3892445582586428,0.42765685019206146,0.3578745198463508,0.04087028201741599,0.35680751173708913,0.11887426573116062,0.34724711907810496,0.17823551058609727,0.3177336747759283,0.2641908975177659,0.36958849053919446,0.3812404238586874,0.44173422420832625
+3.0,294,0.33162612035851474,0.3405889884763124,0.3681177976952625,0.4039692701664533,0.33162612035851474,0.038588929588341196,0.3322663252240717,0.11297571247042615,0.3250960307298335,0.17031603260342357,0.29769526248399486,0.2554519940509474,0.3444845842733163,0.3580070743078956,0.42093121870079336

eval/Information-Retrieval_evaluation_dim_64_results.csv CHANGED Viewed

@@ -1,7 +1,4 @@
 epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
-1.0,98,0.25480153649167736,0.2605633802816901,0.29257362355953903,0.33034571062740076,0.25480153649167736,0.027436091074072376,0.2554417413572343,0.08147833022110194,0.25416133162612037,0.12742618628634134,0.241101152368758,0.20345713326771228,0.268041582830315,0.28207944797157253,0.34000696782787143
-2.0,196,0.24007682458386684,0.2471190781049936,0.26632522407170295,0.30985915492957744,0.24007682458386684,0.02752517367039453,0.24093043107127612,0.08099552823400773,0.2367477592829705,0.12372044634475811,0.22099871959026893,0.18855203634297554,0.25156494522691686,0.26238472694967735,0.3270997667027699
-3.0,294,0.2119078104993598,0.21638924455825864,0.23623559539052497,0.26312419974391804,0.2119078104993598,0.021909848472067953,0.21233461374306442,0.06487593892879456,0.20947503201024328,0.09950245391323564,0.19590268886043533,0.14975275404193011,0.22060240229254297,0.22921012374813438,0.2778029194657925
-1.0,98,0.2740076824583867,0.27848911651728553,0.30153649167733676,0.3354673495518566,0.2740076824583867,0.03167890172057568,0.27315407597097735,0.09267023360511464,0.2670934699103713,0.14048625468314752,0.24571062740076827,0.21092883720941633,0.28429414873076814,0.29402896525927075,0.3539045084602349
-2.0,196,0.28040973111395645,0.28297055057618437,0.3072983354673495,0.3348271446862996,0.28040973111395645,0.03187808455878807,0.27955612462654716,0.09363361347149868,0.27247119078105,0.14192536615474802,0.24878361075544175,0.2128007008801171,0.28944678170030247,0.2991224720529457,0.35085623648833997
-3.0,294,0.25480153649167736,0.2605633802816901,0.2906530089628681,0.323303457106274,0.25480153649167736,0.031011767980561305,0.25480153649167736,0.09100224310580617,0.25006402048655574,0.13823759538062028,0.23079385403329064,0.21011380307216662,0.266841960856045,0.28022682237950125,0.3332689262079475

 epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
+1.0,98,0.23175416133162613,0.23879641485275288,0.2612035851472471,0.29833546734955185,0.23175416133162613,0.028384798943475897,0.23218096457533077,0.08325514613360847,0.22740076824583869,0.12720688223912358,0.20864276568501922,0.19540887275051927,0.24303802613661746,0.2548721998123125,0.3151829220617657
+2.0,196,0.26504481434058896,0.26952624839948786,0.29257362355953903,0.3322663252240717,0.26504481434058896,0.030859353047043094,0.2646180110968843,0.09025134722734952,0.25813060179257363,0.13616521781869687,0.2385403329065301,0.20564514911963047,0.27606167306871515,0.28738876488409937,0.3471195034779171
+3.0,294,0.25096030729833546,0.2560819462227913,0.2900128040973111,0.32970550576184376,0.25096030729833546,0.0281516535128601,0.2507469056764831,0.08222758111049663,0.24788732394366192,0.12591556967755266,0.23604353393085786,0.19940598657336947,0.2645008942544151,0.27958348757665724,0.33353078928131286

eval/Information-Retrieval_evaluation_dim_768_results.csv CHANGED Viewed

@@ -1,7 +1,4 @@
 epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
-1.0,98,0.3674775928297055,0.3738796414852753,0.41165172855313703,0.4558258642765685,0.3674775928297055,0.04090312467372361,0.3681177976952625,0.12089217713355141,0.3624839948783611,0.18502530356129382,0.3385403329065301,0.28508929243050846,0.3827741702741699,0.3991780077769589,0.46526581757220226
-2.0,196,0.3201024327784891,0.33034571062740076,0.36555697823303457,0.40781049935979513,0.3201024327784891,0.0368742412270932,0.3215962441314554,0.1088101072503079,0.31766965428937255,0.16683683168769528,0.29769526248399486,0.2575427865947166,0.33594394650732656,0.3531117937333453,0.41567574230937915
-3.0,294,0.3002560819462228,0.3085787451984635,0.3405889884763124,0.38348271446862997,0.3002560819462228,0.03354719734205534,0.30153649167733676,0.09937908091364656,0.29769526248399486,0.15284430642322494,0.27567221510883483,0.23085365176940398,0.31442747393451553,0.3279302500611031,0.3911512630662361
-1.0,98,0.3591549295774648,0.3649167733674776,0.3892445582586428,0.4334186939820743,0.3591549295774648,0.04250079684114586,0.3587281263337601,0.12462187901616553,0.34852752880921894,0.1875478484365334,0.31670934699103714,0.27695909667507057,0.37149335406377615,0.38308181752122755,0.4493001842217619
-2.0,196,0.32970550576184376,0.33418693982074266,0.36427656850192064,0.3994878361075544,0.32970550576184376,0.040955758827011135,0.3288518992744345,0.12009305539695316,0.31997439180537773,0.18142212378067016,0.2877720870678617,0.26685683005601735,0.3415124585899229,0.35370573856938964,0.4160652625925415
-3.0,294,0.3072983354673495,0.31049935979513443,0.3444302176696543,0.37451984635083224,0.3072983354673495,0.03940235994624546,0.3060179257362356,0.11527075559959522,0.29795134443021765,0.17393586357387436,0.26677336747759284,0.2544826642178083,0.3188075422230347,0.3310954692046881,0.3944113472988561

 epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
+1.0,98,0.36619718309859156,0.37516005121638923,0.4014084507042254,0.44302176696542894,0.36619718309859156,0.042908107176418055,0.3666239863422962,0.12573828441229515,0.35761843790012804,0.18984022934199501,0.32541613316261203,0.2828362934197418,0.37943672133812956,0.3923099208699586,0.4592162636155952
+2.0,196,0.3546734955185659,0.36107554417413573,0.3860435339308579,0.4186939820742638,0.3546734955185659,0.04034211902742892,0.354033290653009,0.11739647757212558,0.34494238156209983,0.17629643014791566,0.3146606914212548,0.2626701106236,0.36586844298111887,0.3776871349900537,0.4380682423691407
+3.0,294,0.32842509603072984,0.3361075544174136,0.36299615877080665,0.4039692701664533,0.32842509603072984,0.03923116896195945,0.32863849765258213,0.1147561273639918,0.3199743918053777,0.17206648000872884,0.2928297055057618,0.25514859248143046,0.3415119504908234,0.35462738075585315,0.4227568005919578

model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b8b8678a200e1ec3a97ec08f700f81cc6660e581d09862b47b576834736c0668
 size 2239607176

 version https://git-lfs.github.com/spec/v1
+oid sha256:ad96896c31a7a57d2d2591979a3de4018f6e0a81c8eb47198774b1b88cd52c55
 size 2239607176

tokenizer_config.json CHANGED Viewed

@@ -47,16 +47,9 @@
   "eos_token": "</s>",
   "extra_special_tokens": {},
   "mask_token": "<mask>",
-  "max_length": 512,
   "model_max_length": 512,
-  "pad_to_multiple_of": null,
   "pad_token": "<pad>",
-  "pad_token_type_id": 0,
-  "padding_side": "right",
   "sep_token": "</s>",
-  "stride": 0,
   "tokenizer_class": "XLMRobertaTokenizer",
-  "truncation_side": "right",
-  "truncation_strategy": "longest_first",
   "unk_token": "<unk>"
 }

   "eos_token": "</s>",
   "extra_special_tokens": {},
   "mask_token": "<mask>",
   "model_max_length": 512,
   "pad_token": "<pad>",
   "sep_token": "</s>",
   "tokenizer_class": "XLMRobertaTokenizer",
   "unk_token": "<unk>"
 }

training_args.bin CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:739b4a0a62fdf782034d2ababe5e5ea588023ed6263f2604e31385fc77a8faab
 size 6097

 version https://git-lfs.github.com/spec/v1
+oid sha256:8a0318feaae2d8aeaebeec5835b4bc77eb79a026385dfb908828064d2f4fd294
 size 6097