CrossEncoder based on FacebookAI/roberta-base

This is a Cross Encoder model finetuned from FacebookAI/roberta-base on the weak-labels-wiki dataset using the sentence-transformers library. It computes scores for pairs of texts, which can be used for text reranking and semantic search.

Model Details

Model Description

Model Type: Cross Encoder
Base model: FacebookAI/roberta-base
Maximum Sequence Length: 384 tokens
Number of Output Labels: 1 label
Training Dataset:
- weak-labels-wiki

Model Sources

Documentation: Sentence Transformers Documentation
Documentation: Cross Encoder Documentation
Repository: Sentence Transformers on GitHub
Hugging Face: Cross Encoders on Hugging Face

Usage

Direct Usage (Sentence Transformers)

First install the Sentence Transformers library:

pip install -U sentence-transformers

Then you can load this model and run inference.

from sentence_transformers import CrossEncoder

# Download from the 🤗 Hub
model = CrossEncoder("cross_encoder_model_id")
# Get scores for pairs of texts
pairs = [
    ['q247925', 'linux__Watchdog_timer_P0020'],
    ['q216149', 'smartphones__Samsung_Galaxy_Z_Flip_P0003'],
    ['q174658', 'great_depression__Great_Depression_P0184'],
    ['q062615', 'barack_obama__2008_Democratic_Party_vice_presidential_candidate_selection_P0000'],
    ['q054198', 'donald_trump__Business_projects_of_Donald_Trump_in_Russia_P0007'],
]
scores = model.predict(pairs)
print(scores.shape)
# (5,)

# Or rank different texts based on similarity to a single text
ranks = model.rank(
    'q247925',
    [
        'linux__Watchdog_timer_P0020',
        'smartphones__Samsung_Galaxy_Z_Flip_P0003',
        'great_depression__Great_Depression_P0184',
        'barack_obama__2008_Democratic_Party_vice_presidential_candidate_selection_P0000',
        'donald_trump__Business_projects_of_Donald_Trump_in_Russia_P0007',
    ]
)
# [{'corpus_id': ..., 'score': ...}, {'corpus_id': ..., 'score': ...}, ...]

Training Details

Training Dataset

weak-labels-wiki

Dataset: weak-labels-wiki at a064a52
Size: 2,152,512 training samples
Columns: query_id, pos_doc_id, neg_doc_id, neg_kind, sentence_0_input_ids, sentence_0_attention_mask, sentence_1_input_ids, and sentence_1_attention_mask

Approximate statistics based on the first 1000 samples:

	query_id	pos_doc_id	neg_doc_id	neg_kind	sentence_0_input_ids	sentence_0_attention_mask	sentence_1_input_ids	sentence_1_attention_mask
type	string	string	string	string	torch.Tensor	torch.Tensor	torch.Tensor	torch.Tensor
details	min: 7 characters mean: 7.0 characters max: 7 characters	min: 17 characters mean: 38.6 characters max: 82 characters	min: 17 characters mean: 40.08 characters max: 86 characters	min: 4 characters mean: 4.0 characters max: 4 characters

Samples:

query_id	pos_doc_id	neg_doc_id	neg_kind	sentence_0_input_ids	sentence_0_attention_mask	sentence_1_input_ids	sentence_1_attention_mask
`q187533`	`deep_learning__Deep_Learning_Super_Sampling_P0000`	`deep_learning__Neural_processing_unit_P0000`	`hard`	tensor([ 0, 35166, 2239, 18520, 998, 2, 2, 35166, 13807, 1582, 1960, 20418, 36, 26109, 8108, 43, 16, 10, 10606, 9, 588, 12, 958, 1844, 2239, 2274, 25387, 8, 62, 3866, 8279, 4233, 2226, 30, 18520, 14, 32, 577, 11, 10, 346, 9, 569, 426, 4, 20, 724, 9, 209, 4233, 16, 7, 1157, 5, 1647, 9, 5, 12774, 4116, 7, 422, 23, 10, 795, 3547, 13, 1130, 819, 6, 8, 172, 40182, 10, 723, 3547, 2274, 31, 42, 14, 36612, 34129, 5, 276, 672, 9, 4617, 25, 114, 5, 2274, 56, 57, 18728, 23, 42, 723, 3547, 4, 152, 2386, 13, 723, 41806, 9629, 8, 73, 368, 5120, 1162, 13, 10, 576, 4195, 3547, 6, 6122, 15, 3018, 12832, 4, 404, 6808, 9, 13925, 8108, 32, 577, 15, 70, 40810, 12, 20417, 3591, 31, 18520, 11, 2800, 4867, 4, 635, 6, 5, 37280, 17362, 1905, 16, 129, 2800, 15, 843, 651, 37658, 50, 13964, 8, 19268, 37280, 17362, 16, 129, 577, 15, 654, 651, 37658, 4, 45994, 7298, 45994, 18520, 20454, 13925, 8108, 25, 10, 762, 1905, 9, 5, 36988, 291, 651, 3591, 77, 51, 1660, 11, 772, 199, 4, 497, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])	tensor([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])	tensor([ 0, 35166, 2239, 18520, 998, 2, 2, 250, 26739, 5774, 1933, 36, 487, 16821, 238, 67, 684, 25, 4687, 31463, 50, 1844, 2239, 10655, 6, 16, 10, 1380, 9, 14120, 6554, 31463, 50, 3034, 467, 1887, 7, 10107, 7350, 2316, 36, 15238, 43, 8, 3563, 2239, 2975, 6, 217, 7350, 26739, 4836, 8, 3034, 3360, 4, 45994, 7627, 45994, 2667, 3508, 16, 1169, 7, 14146, 11189, 416, 5389, 4687, 3092, 36, 179, 23861, 43, 50, 7, 2341, 4687, 3092, 4, 2667, 2975, 680, 16964, 13, 20721, 6, 3742, 9, 383, 6, 8, 414, 12, 28447, 50, 9626, 12, 9756, 8558, 4, 252, 32, 747, 171, 7293, 50, 34999, 7191, 8, 1056, 15, 614, 12, 5234, 37938, 43585, 6, 5808, 414, 19322, 41885, 6, 50, 11, 12, 44290, 11730, 9388, 4, 287, 9, 15294, 6, 10, 3924, 341, 13516, 1043, 11798, 12, 8425, 4687, 6818, 9326, 6638, 6, 5, 18520, 289, 1866, 22794, 6, 6308, 7281, 9, 6685, 9, 256, 3196, 597, 3935, 29, 4, 47408, 7653, 2110, 47408, 4687, 27416, 3629, 32, 341, 11, 1830, 2110, 215, 25, 1257, 14825, 6, 15297, 4687, 8186, 11, 13854, 337, 8, 234, 16821, 29, 6, 8820, 6, 8, 1204, 11699, 7466, 6, 8, 450, 11, 171, 1257, 28630, 6, 10805, 6, 3797, 6, 8, 1204, 255, 35354, 4368, 17852, 4, 243, 16, 55, 682, 36, 31362, 102, 8157, 43, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])	tensor([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
`q248783`	`linux__64-bit_computing_P0061`	`linux__Microkernel_P0009`	`hard`	tensor([ 0, 11828, 1322, 15826, 8, 32469, 13, 709, 6216, 2, 2, 1990, 32469, 40, 422, 15, 167, 1743, 4, 20, 2107, 12, 5881, 7952, 9, 18146, 33, 57, 2928, 30, 1257, 11, 32469, 19963, 1243, 36, 698, 4, 996, 322, 15826, 8, 144, 97, 47093, 12, 3341, 1633, 1743, 6, 8, 5, 230, 8, 230, 42964, 3944, 42433, 13, 106, 6, 33, 2800, 4430, 12, 5881, 17852, 13, 171, 107, 4, 1876, 2975, 8, 18146, 13, 167, 4818, 32, 490, 12, 17747, 2257, 6, 1982, 11, 230, 8, 230, 42964, 6, 98, 14, 114, 51, 32, 4430, 12, 5881, 12, 22725, 6, 51, 64, 28, 11603, 88, 4430, 12, 5881, 7952, 4, 152, 1300, 12, 805, 3854, 1421, 6, 19, 41, 9723, 15, 7690, 8255, 6, 817, 7265, 9, 2502, 2257, 13, 167, 1633, 1743, 540, 9, 41, 696, 4, 45994, 4430, 12, 5881, 414, 3092, 45994, 96, 2107, 12, 5881, 1767, 6, 39715, 8, 414, 3505, 215, 25, 49074, 3489, 33, 5, 276, 5933, 4, 152, 16, 45, 4784, 1528, 15, 4430, 12, 5881, 6271, 4, 16038, 154, 414, 3505, 11, 8326, 11991, 215, 25, 230, 8, 63, 29285, 215, 25, 230, 42964, 8, 44676, 12, 347, 189, 4634, 173, 15, 2107, 12, 5881, 42993, 53, 45, 15, 4430, 12, 5881, 42993, 4, 96, 171, 8326, 11534, 13, 230, 8, 230, 12, 38871, 11991, 15, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])	tensor([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])	tensor([ 0, 11828, 1322, 15826, 8, 32469, 13, 709, 6216, 2, 2, 11802, 12, 8056, 9439, 34751, 1170, 56, 1249, 6, 1712, 1257, 18, 32469, 6, 703, 11, 5155, 6, 202, 2939, 10, 9284, 34751, 373, 1577, 487, 791, 6, 61, 15678, 10, 4008, 10639, 36, 11108, 21676, 43, 8192, 597, 73, 134, 18, 9439, 34751, 36, 3196, 597, 20149, 262, 4, 246, 34751, 43, 19, 3260, 31, 163, 6243, 2604, 9482, 6, 8, 42, 34751, 16, 67, 341, 11, 6894, 6, 30016, 3196, 6, 8, 1183, 3196, 4, 6039, 19815, 6, 1158, 19, 19815, 155, 4, 134, 8, 3348, 19, 6039, 365, 6, 2939, 10, 9284, 34751, 1521, 4, 287, 9, 1125, 6, 5, 9439, 12, 805, 45928, 289, 6831, 16, 67, 12628, 8, 1165, 11, 3044, 7952, 9, 10832, 15826, 8, 45534, 4, 2223, 538, 173, 15, 5177, 330, 47909, 56, 2743, 1249, 6, 9280, 268, 1143, 709, 4, 8630, 10, 55, 26794, 1548, 7, 5, 936, 6, 217, 6559, 3260, 8, 13304, 15, 5, 10655, 7, 10914, 14198, 6329, 2800, 11, 2257, 669, 7, 10, 92, 651, 9, 5177, 330, 47909, 19, 8617, 2782, 819, 4, 10719, 330, 47909, 32, 3615, 1330, 7, 1931, 1638, 47909, 4, 252, 67, 33, 203, 11, 1537, 19, 8944, 22074, 6, 53, 5, 5442, 146, 117, 2026, 7, 15970, 6948, 8, 32, 14120, 7, 3117, 6229, 6271, 131, 5, 226, 306, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])	tensor([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
`q091993`	`youtube__Amazon_Prime_Video_P0005`	`napoleon__Horrible_Histories__2009_TV_series__P0063`	`hard`	tensor([ 0, 10836, 38, 4016, 10, 623, 1771, 3082, 6717, 15, 1645, 1489, 116, 2, 2, 43232, 6, 10005, 5331, 8, 10804, 14735, 7, 5, 1489, 26596, 5338, 544, 4, 374, 392, 883, 6, 1125, 6, 1645, 12680, 19, 1569, 4535, 22299, 12290, 7, 4615, 2213, 9, 4133, 15, 5, 544, 4, 374, 502, 508, 6, 1125, 6, 1645, 585, 10, 432, 19, 5768, 12, 20439, 16541, 12, 448, 19777, 7, 4615, 4133, 8, 2384, 924, 15, 5, 1489, 26596, 5338, 544, 4, 374, 550, 291, 6, 1125, 6, 1645, 585, 10, 432, 19, 6123, 11712, 4, 10276, 7, 4615, 80, 924, 20, 580, 11384, 8, 4967, 18174, 8992, 15, 1489, 26596, 5338, 4, 374, 772, 204, 6, 1125, 6, 1645, 1419, 10, 432, 19, 582, 12, 859, 41605, 4238, 14230, 3181, 36, 8310, 684, 25, 20405, 2744, 8, 187, 494, 8157, 2164, 30, 1645, 1495, 43, 7, 1905, 4133, 15, 49, 5230, 544, 6, 11, 10, 517, 7, 3429, 49, 11439, 3909, 4, 374, 719, 601, 6, 1125, 6, 1645, 585, 10, 432, 19, 6980, 13610, 5149, 7, 4615, 80, 924, 31, 27848, 6, 20, 2893, 19780, 8, 35647, 39191, 4, 96, 644, 1014, 6, 1645, 1419, 10, 432, 19, 83, 2744, 717, 14641, 7, 4615, 924, 31, 5, 83, 947, 717, 6, 20, 6479, 10486, 5331, 6, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])	tensor([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])	tensor([ 0, 10836, 38, 4016, 10, 623, 1771, 3082, 6717, 15, 1645, 1489, 116, 2, 2, 12338, 990, 1089, 408, 18, 1012, 651, 6, 8, 21, 4173, 23, 440, 4, 290, 11, 10, 1122, 3107, 654, 889, 2633, 423, 5, 276, 76, 30, 5331, 4934, 4, 45994, 19888, 8, 804, 8255, 45994, 404, 292, 651, 9, 5, 1461, 311, 6, 2704, 5, 22, 12645, 1766, 36, 725, 42032, 43, 3672, 1297, 22, 500, 808, 636, 19631, 39164, 113, 359, 5, 22, 597, 4070, 2650, 1234, 623, 1771, 3672, 113, 8, 22, 39389, 24786, 1619, 113, 33, 57, 703, 15, 6131, 132, 19888, 30, 132, 1342, 23801, 13, 5, 3295, 6, 258, 15529, 8, 25, 35657, 3880, 4, 22, 39389, 24786, 31862, 9023, 108, 1776, 10772, 1643, 113, 359, 5, 22, 19451, 3672, 113, 33, 648, 7, 1325, 10, 184, 569, 800, 4, 4028, 651, 6, 25, 157, 25, 5, 22, 12645, 1766, 3672, 113, 8, 22, 19451, 3672, 1297, 32, 67, 577, 13, 4016, 31, 5, 987, 14734, 1400, 4, 287, 9, 902, 777, 6, 70, 7585, 31, 3265, 112, 2383, 246, 58, 577, 13, 4016, 7, 470, 7768, 15, 1645, 4, 175, 22, 47193, 5338, 113, 544, 4, 45994, 26317, 12, 10816, 45994, 96, 1466, 6, 10, 6287, 1529, 177, 311, 6, 6746, 24786, 31862, 9023, 35, 272, 4405, 3100, 6, 21, 1660, 15, 6933, 3573, 4, 21371, 9212, 44953, 7618, 30, 14399, 1012, 8, 7801, 14888, 6, 5, 311, 21, 1029, 12, 11438, 196, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])	tensor([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])

Loss: main.PairwiseMarginLoss

Evaluation Dataset

weak-labels-wiki

Dataset: weak-labels-wiki at a064a52
Size: 21,743 evaluation samples
Columns: query_id, pos_doc_id, neg_doc_id, neg_kind, sentence_0_input_ids, sentence_0_attention_mask, sentence_1_input_ids, and sentence_1_attention_mask

Approximate statistics based on the first 1000 samples:

	query_id	pos_doc_id	neg_doc_id	neg_kind	sentence_0_input_ids	sentence_0_attention_mask	sentence_1_input_ids	sentence_1_attention_mask
type	string	string	string	string	torch.Tensor	torch.Tensor	torch.Tensor	torch.Tensor
details	min: 7 characters mean: 7.0 characters max: 7 characters	min: 17 characters mean: 39.17 characters max: 107 characters	min: 17 characters mean: 40.11 characters max: 113 characters	min: 4 characters mean: 4.0 characters max: 4 characters

Samples:

query_id	pos_doc_id	neg_doc_id	neg_kind	sentence_0_input_ids	sentence_0_attention_mask	sentence_1_input_ids	sentence_1_attention_mask
`q247925`	`linux__Watchdog_timer_P0020`	`linux__Dd__Unix__P0017`	`hard`	tensor([ 0, 6179, 473, 15826, 3679, 467, 12328, 8, 414, 2752, 2, 2, 179, 5, 403, 9, 5, 15826, 1633, 467, 6, 10, 3018, 12, 25414, 10707, 48448, 189, 1622, 3151, 5, 10707, 27405, 396, 4655, 143, 3457, 4, 287, 251, 25, 5, 48448, 1237, 6329, 6, 5, 467, 40, 28, 4371, 136, 1473, 467, 12328, 215, 25, 10, 34751, 9810, 4, 598, 10933, 540, 3814, 28853, 6, 5, 48448, 64, 3008, 3457, 14, 1719, 1337, 5894, 9, 5, 467, 1881, 6, 217, 5799, 7265, 36, 242, 4, 571, 482, 3783, 6, 2870, 14617, 6, 21032, 86, 238, 1283, 9, 421, 609, 1940, 36, 242, 4, 571, 482, 467, 2955, 991, 1790, 878, 6, 2167, 6773, 145, 1455, 50, 4752, 238, 27169, 1295, 6, 8, 1546, 1940, 4, 12630, 6953, 9, 10, 1447, 1296, 6, 5, 3034, 189, 2120, 7, 3008, 10, 13931, 9, 31378, 2163, 223, 2257, 797, 6, 29681, 19, 10, 2257, 12, 179, 4933, 1070, 18660, 4, 318, 5, 2257, 10578, 7, 32550, 10, 18660, 6, 5, 6554, 10707, 35809, 93, 114, 577, 93, 40, 25386, 8, 32550, 10, 6554, 18821, 4, 96, 1683, 6, 42, 16, 10, 7268, 661, 1580, 10707, 35809, 11, 61, 5, 2257, 16755, 5, 78, 8, 5, 6554, 305, 23858, 5, 507, 1289, 4, 96, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])	tensor([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])	tensor([ 0, 6179, 473, 15826, 3679, 467, 12328, 8, 414, 2752, 2, 2, 241, 397, 4086, 4, 13021, 543, 21675, 6790, 5585, 10, 27443, 4594, 3175, 5936, 1887, 7, 13140, 8, 31328, 24300, 358, 6500, 8, 34949, 4745, 9, 10, 1305, 4, 85, 189, 67, 173, 13, 103, 2705, 12, 4897, 6790, 36, 39837, 6790, 322, 287, 9, 193, 6, 24, 473, 45, 173, 15, 10478, 7462, 6790, 3486, 15, 27443, 6282, 7462, 6180, 4, 520, 577, 6, 42, 16, 258, 3845, 87, 634, 47821, 6, 8, 55, 2823, 4, 374, 15826, 6271, 24, 16, 6500, 1241, 5, 1368, 43923, 4526, 5936, 18, 480, 15506, 12, 254, 3175, 12, 15477, 16325, 1973, 4, 20, 27373, 586, 1523, 1533, 42674, 39651, 6, 25, 157, 25, 55, 2823, 43762, 9, 1736, 6773, 4, 47408, 5423, 2752, 47408, 5423, 2752, 6890, 2600, 31, 10, 1305, 19, 103, 1667, 2905, 34949, 4, 20, 5936, 16, 10, 205, 2564, 19, 42, 633, 19, 63, 9538, 26756, 36, 42876, 43, 8, 97, 614, 12, 4483, 9629, 4, 20, 21857, 47821, 6, 959, 6, 16, 38734, 7, 304, 25, 5, 3018, 34, 7, 1166, 5, 5849, 3731, 8, 24704, 15756, 5, 3806, 14, 64, 28, 1166, 4, 20, 881, 1803, 1836, 67, 4971, 5, 17227, 42664, 9, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])	tensor([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
`q216149`	`smartphones__Samsung_Galaxy_Z_Flip_P0003`	`smartphones__Samsung_Galaxy_Z_Fold_4_P0000`	`hard`	tensor([ 0, 23242, 1851, 5, 806, 639, 14789, 868, 7466, 2, 2, 5632, 10, 4136, 10490, 1122, 7, 5, 5325, 41303, 6, 13918, 30, 3797, 19, 3183, 31, 1811, 5229, 5680, 6, 61, 16, 22, 25617, 634, 41, 18420, 4945, 609, 7, 6292, 63, 8243, 8, 28327, 1297, 8, 22993, 19, 10, 22, 19423, 1468, 62, 7, 41, 15120, 5581, 7, 3042, 10, 4292, 46743, 25718, 9164, 12627, 4699, 10352, 16, 341, 13, 5, 124, 9217, 4, 20, 525, 14782, 16, 5, 78, 14789, 868, 4368, 7, 304, 10, 4049, 2332, 6, 150, 986, 14789, 868, 4247, 215, 25, 5, 23034, 21965, 338, 8, 5, 5325, 41303, 33, 341, 4136, 8612, 4, 8630, 10, 4049, 2332, 775, 11, 10, 55, 18300, 2441, 6, 8, 13458, 5, 2441, 8633, 3175, 11, 5, 29556, 477, 4, 20, 33503, 9562, 16, 13813, 19, 38874, 32902, 1887, 7, 489, 8402, 66, 131, 3797, 5211, 5, 14789, 9562, 25, 3117, 62, 7, 1878, 6, 151, 2939, 4, 20, 2187, 606, 11, 155, 8089, 13, 5, 20066, 1732, 61, 32, 15187, 21706, 6, 15187, 1378, 8, 15187, 2610, 4, 85, 67, 606, 11, 132, 8089, 13, 5, 195, 534, 1732, 61, 32, 42929, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])	tensor([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])	tensor([ 0, 23242, 1851, 5, 806, 639, 14789, 868, 7466, 2, 2, 133, 3797, 5325, 525, 41303, 204, 36, 620, 4360, 1538, 25, 3797, 5325, 525, 41303, 306, 6, 1088, 25, 3797, 5325, 41303, 204, 11, 1402, 13560, 43, 16, 10, 14789, 868, 4368, 14, 16, 233, 9, 5, 3797, 5325, 525, 651, 4, 85, 21, 585, 23, 5, 830, 8157, 5403, 9, 5325, 1890, 21330, 2863, 5, 5325, 525, 14782, 204, 4, 85, 21, 703, 8960, 15, 830, 564, 6, 8157, 6, 25, 5, 10359, 7, 5, 5325, 525, 41303, 155, 4, 45994, 38212, 45994, 47408, 7438, 47408, 20, 525, 41303, 204, 18, 15705, 2332, 8, 124, 2798, 304, 12627, 4699, 10352, 41269, 687, 30787, 11187, 5, 14789, 868, 8725, 2332, 16, 156, 9, 3797, 18, 14101, 22, 45611, 12, 11329, 179, 10352, 113, 19, 80, 11775, 21817, 4136, 13171, 4631, 24, 6, 5, 299, 9, 61, 16, 10, 3190, 868, 2441, 32747, 4, 20, 525, 41303, 204, 34, 41, 6442, 1000, 398, 21691, 5224, 2591, 691, 13, 514, 5910, 6, 19, 8402, 5910, 45, 145, 5211, 4, 20, 15705, 5120, 16, 11236, 31, 9757, 6, 22472, 25, 128, 47936, 37280, 108, 30, 3797, 4, 20, 3797, 5325, 525, 41303, 204, 16, 577, 11, 237, 8089, 35, 30099, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])	tensor([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
`q174658`	`great_depression__Great_Depression_P0184`	`great_depression__The_Great_Depression__America__1929_1941_P0003`	`hard`	tensor([ 0, 19065, 23384, 5984, 1915, 998, 2, 2, 38261, 9, 1005, 6, 37708, 2383, 1646, 3416, 36, 43587, 43, 47408, 315, 532, 8, 896, 47408, 8639, 7864, 6, 6227, 4, 15387, 11, 5, 2933, 4832, 10, 4106, 750, 9, 5, 2860, 23384, 36, 23301, 43, 804, 10310, 154, 5, 25900, 1554, 35, 26476, 8, 33262, 9, 5, 1505, 33967, 13, 25900, 15773, 4011, 4, 6056, 4, 26873, 2383, 1646, 3079, 4, 504, 33505, 19553, 36, 134, 2233, 322, 497, 5, 6338, 26844, 9, 663, 6, 589, 9, 663, 40071, 3672, 42121, 4, 4537, 15571, 3432, 6, 610, 12394, 6, 20, 2860, 30522, 6, 32638, 36, 1646, 4283, 238, 1406, 804, 2610, 6712, 6, 1738, 6, 20, 2860, 23384, 35, 20, 315, 532, 11, 5, 2032, 9211, 918, 36, 44808, 43, 5076, 6, 871, 6, 7978, 31, 18019, 35, 20, 470, 1806, 11, 23384, 8, 1771, 6, 32638, 12, 45391, 36, 17472, 43, 1509, 14563, 4468, 6, 2668, 6, 8, 2431, 20582, 4, 20, 2860, 23384, 32638, 2383, 1646, 3170, 36, 46207, 154, 121, 4, 104, 4, 7298, 43, 36, 24789, 43, 804, 6, 13, 1692, 1304, 4, 5275, 6, 8397, 687, 4, 23384, 1502, 1829, 35, 1740, 188, 24636, 149, 188, 10979, 6, 32638, 2383, 1646, 4006, 36, 1646, 3706, 238, 204, 5379, 33906, 482, 10675, 1953, 9, 5, 121, 4, 104, 4, 866, 804, 1223, 354, 6, 9317, 83, 4, 20, 2860, 23384, 8, 5, 188, 10979, 4832, 730, 18, 866, 11, 1486, 36, 22748, 43, 13, 5929, 1304, 4, 804, 11881, 9063, 6, 83, 4, 381, 4, 20, 1563, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])	tensor([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])	tensor([ 0, 19065, 23384, 5984, 1915, 998, 2, 2, 42425, 49, 1503, 7, 17800, 50, 5, 188, 10979, 6, 1509, 717, 25091, 5193, 1523, 10, 9893, 1217, 9, 5, 2860, 23384, 8, 63, 913, 578, 261, 390, 25, 157, 25, 604, 6, 909, 25, 157, 25, 1104, 6, 15, 1406, 2040, 6, 941, 5, 822, 6, 8, 6, 144, 524, 5881, 9997, 6, 15, 470, 3266, 72, 2090, 2852, 373, 5, 1040, 22, 415, 683, 10, 10675, 173, 9, 10560, 6, 10, 20902, 527, 6, 8, 10, 2200, 1461, 11930, 9, 1966, 14, 34, 10, 205, 432, 9, 8708, 21623, 72, 20, 1040, 21, 566, 5, 78, 7, 304, 1406, 2040, 6, 941, 822, 6, 25, 41, 505, 5799, 11, 2969, 5, 6711, 9, 10, 86, 4, 20, 1040, 34, 4711, 5861, 11, 5780, 187, 63, 5362, 4, 83, 200, 5403, 21, 1027, 11, 9095, 6, 24634, 8231, 19, 5, 799, 12, 7755, 24098, 2384, 651, 6, 20, 2860, 23384, 6, 13, 61, 42, 1040, 21, 10, 538, 5799, 4, 83, 564, 212, 12, 2279, 42797, 5403, 6, 19, 10, 5145, 92, 7740, 12818, 5, 4215, 981, 62, 7, 5, 613, 6277, 9, 2266, 19, 167, 11, 5, 18283, 29, 14, 669, 7, 5, 2860, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])	tensor([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])

Loss: main.PairwiseMarginLoss

Training Hyperparameters

Non-Default Hyperparameters

eval_strategy: steps
per_device_train_batch_size: 290
per_device_eval_batch_size: 128
learning_rate: 1e-05
weight_decay: 0.02
max_grad_norm: 0.5
num_train_epochs: 10.0
lr_scheduler_type: cosine
warmup_ratio: 0.03
bf16: True
dataloader_num_workers: 6
remove_unused_columns: False
load_best_model_at_end: True
optim: adamw_torch
dataloader_persistent_workers: True

All Hyperparameters

Click to expand

overwrite_output_dir: False
do_predict: False
eval_strategy: steps
prediction_loss_only: True
per_device_train_batch_size: 290
per_device_eval_batch_size: 128
per_gpu_train_batch_size: None
per_gpu_eval_batch_size: None
gradient_accumulation_steps: 1
eval_accumulation_steps: None
torch_empty_cache_steps: None
learning_rate: 1e-05
weight_decay: 0.02
adam_beta1: 0.9
adam_beta2: 0.999
adam_epsilon: 1e-08
max_grad_norm: 0.5
num_train_epochs: 10.0
max_steps: -1
lr_scheduler_type: cosine
lr_scheduler_kwargs: {}
warmup_ratio: 0.03
warmup_steps: 0
log_level: passive
log_level_replica: warning
log_on_each_node: True
logging_nan_inf_filter: True
save_safetensors: True
save_on_each_node: False
save_only_model: False
restore_callback_states_from_checkpoint: False
no_cuda: False
use_cpu: False
use_mps_device: False
seed: 42
data_seed: None
jit_mode_eval: False
bf16: True
fp16: False
fp16_opt_level: O1
half_precision_backend: auto
bf16_full_eval: False
fp16_full_eval: False
tf32: None
local_rank: 0
ddp_backend: None
tpu_num_cores: None
tpu_metrics_debug: False
debug: []
dataloader_drop_last: False
dataloader_num_workers: 6
dataloader_prefetch_factor: None
past_index: -1
disable_tqdm: False
remove_unused_columns: False
label_names: None
load_best_model_at_end: True
ignore_data_skip: False
fsdp: []
fsdp_min_num_params: 0
fsdp_config: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
fsdp_transformer_layer_cls_to_wrap: None
accelerator_config: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
parallelism_config: None
deepspeed: None
label_smoothing_factor: 0.0
optim: adamw_torch
optim_args: None
adafactor: False
group_by_length: False
length_column_name: length
project: huggingface
trackio_space_id: trackio
ddp_find_unused_parameters: None
ddp_bucket_cap_mb: None
ddp_broadcast_buffers: False
dataloader_pin_memory: True
dataloader_persistent_workers: True
skip_memory_metrics: True
use_legacy_prediction_loop: False
push_to_hub: False
resume_from_checkpoint: None
hub_model_id: None
hub_strategy: every_save
hub_private_repo: None
hub_always_push: False
hub_revision: None
gradient_checkpointing: False
gradient_checkpointing_kwargs: None
include_inputs_for_metrics: False
include_for_metrics: []
eval_do_concat_batches: True
fp16_backend: auto
push_to_hub_model_id: None
push_to_hub_organization: None
mp_parameters:
auto_find_batch_size: False
full_determinism: False
torchdynamo: None
ray_scope: last
ddp_timeout: 1800
torch_compile: False
torch_compile_backend: None
torch_compile_mode: None
include_tokens_per_second: False
include_num_input_tokens_seen: no
neftune_noise_alpha: None
optim_target_modules: None
batch_eval_metrics: False
eval_on_start: False
use_liger_kernel: False
liger_kernel_config: None
eval_use_gather_object: False
average_tokens_across_devices: True
prompts: None
batch_sampler: batch_sampler
multi_dataset_batch_sampler: proportional
router_mapping: {}
learning_rate_mapping: {}

Training Logs

Click to expand

Epoch	Step	Training Loss	Validation Loss
0.0067	50	1.0015	-
0.0135	100	1.0	-
0.0202	150	0.9995	-
0.0269	200	0.9982	-
0.0337	250	0.9965	-
0.0404	300	0.9942	-
0.0472	350	0.9858	-
0.0539	400	0.9546	-
0.0606	450	0.8242	-
0.0674	500	0.7001	0.5555
0.0741	550	0.5356	-
0.0808	600	0.4442	-
0.0876	650	0.3845	-
0.0943	700	0.3461	-
0.1010	750	0.3281	-
0.1078	800	0.3069	-
0.1145	850	0.2846	-
0.1212	900	0.2713	-
0.1280	950	0.255	-
0.1347	1000	0.2473	0.1868
0.1415	1050	0.2319	-
0.1482	1100	0.22	-
0.1549	1150	0.2166	-
0.1617	1200	0.2087	-
0.1684	1250	0.1947	-
0.1751	1300	0.1929	-
0.1819	1350	0.1915	-
0.1886	1400	0.1923	-
0.1953	1450	0.1847	-
0.2021	1500	0.179	0.1380
0.2088	1550	0.1783	-
0.2155	1600	0.1691	-
0.2223	1650	0.1688	-
0.2290	1700	0.1626	-
0.2358	1750	0.1585	-
0.2425	1800	0.1579	-
0.2492	1850	0.1576	-
0.2560	1900	0.1466	-
0.2627	1950	0.1518	-
0.2694	2000	0.1612	0.1121
0.2762	2050	0.1465	-
0.2829	2100	0.1395	-
0.2896	2150	0.1372	-
0.2964	2200	0.1323	-
0.3031	2250	0.1312	-
0.3098	2300	0.1324	-
0.3166	2350	0.1329	-
0.3233	2400	0.1284	-
0.3301	2450	0.123	-
0.3368	2500	0.1144	0.0986
0.3435	2550	0.1214	-
0.3503	2600	0.1283	-
0.3570	2650	0.1207	-
0.3637	2700	0.1196	-
0.3705	2750	0.1155	-
0.3772	2800	0.1112	-
0.3839	2850	0.1202	-
0.3907	2900	0.1117	-
0.3974	2950	0.1063	-
0.4041	3000	0.111	0.0829
0.4109	3050	0.108	-
0.4176	3100	0.1094	-
0.4244	3150	0.1072	-
0.4311	3200	0.0976	-
0.4378	3250	0.1076	-
0.4446	3300	0.1049	-
0.4513	3350	0.1109	-
0.4580	3400	0.1043	-
0.4648	3450	0.1021	-
0.4715	3500	0.1034	0.0759
0.4782	3550	0.1036	-
0.4850	3600	0.0975	-
0.4917	3650	0.097	-
0.4985	3700	0.0943	-
0.5052	3750	0.0911	-
0.5119	3800	0.0974	-
0.5187	3850	0.0937	-
0.5254	3900	0.0934	-
0.5321	3950	0.0931	-
0.5389	4000	0.0884	0.0655
0.5456	4050	0.0868	-
0.5523	4100	0.0918	-
0.5591	4150	0.0887	-
0.5658	4200	0.0879	-
0.5725	4250	0.0863	-
0.5793	4300	0.0886	-
0.5860	4350	0.0865	-
0.5928	4400	0.0839	-
0.5995	4450	0.089	-
0.6062	4500	0.0806	0.0617
0.6130	4550	0.0839	-
0.6197	4600	0.084	-
0.6264	4650	0.0836	-
0.6332	4700	0.0753	-
0.6399	4750	0.0779	-
0.6466	4800	0.0825	-
0.6534	4850	0.082	-
0.6601	4900	0.0818	-
0.6668	4950	0.078	-
0.6736	5000	0.0731	0.0581
0.6803	5050	0.0756	-
0.6871	5100	0.0758	-
0.6938	5150	0.0738	-
0.7005	5200	0.0715	-
0.7073	5250	0.0725	-
0.7140	5300	0.0718	-
0.7207	5350	0.0755	-
0.7275	5400	0.071	-
0.7342	5450	0.0723	-
0.7409	5500	0.0766	0.0520
0.7477	5550	0.0708	-
0.7544	5600	0.0766	-
0.7611	5650	0.0692	-
0.7679	5700	0.0731	-
0.7746	5750	0.066	-
0.7814	5800	0.0733	-
0.7881	5850	0.0649	-
0.7948	5900	0.0678	-
0.8016	5950	0.0707	-
0.8083	6000	0.0722	0.0515
0.8150	6050	0.0671	-
0.8218	6100	0.0724	-
0.8285	6150	0.0691	-
0.8352	6200	0.0761	-
0.8420	6250	0.0653	-
0.8487	6300	0.0629	-
0.8554	6350	0.0647	-
0.8622	6400	0.0675	-
0.8689	6450	0.0661	-
0.8757	6500	0.0622	0.0457
0.8824	6550	0.0646	-
0.8891	6600	0.0626	-
0.8959	6650	0.0672	-
0.9026	6700	0.0628	-
0.9093	6750	0.0624	-
0.9161	6800	0.0637	-
0.9228	6850	0.0632	-
0.9295	6900	0.0632	-
0.9363	6950	0.0648	-
0.9430	7000	0.0628	0.0427
0.9498	7050	0.0592	-
0.9565	7100	0.0619	-
0.9632	7150	0.0602	-
0.9700	7200	0.0605	-
0.9767	7250	0.0582	-
0.9834	7300	0.0612	-
0.9902	7350	0.0593	-
0.9969	7400	0.0594	-
1.0036	7450	0.0574	-
1.0104	7500	0.0506	0.0388
1.0171	7550	0.0467	-
1.0238	7600	0.0496	-
1.0306	7650	0.0485	-
1.0373	7700	0.0489	-
1.0441	7750	0.054	-
1.0508	7800	0.0489	-
1.0575	7850	0.051	-
1.0643	7900	0.0497	-
1.0710	7950	0.0493	-
1.0777	8000	0.0519	0.0409
1.0845	8050	0.048	-
1.0912	8100	0.0468	-
1.0979	8150	0.0543	-
1.1047	8200	0.0444	-
1.1114	8250	0.0507	-
1.1181	8300	0.0468	-
1.1249	8350	0.0506	-
1.1316	8400	0.0498	-
1.1384	8450	0.0472	-
1.1451	8500	0.0467	0.0380
1.1518	8550	0.0446	-
1.1586	8600	0.0492	-
1.1653	8650	0.0445	-
1.1720	8700	0.0487	-
1.1788	8750	0.0424	-
1.1855	8800	0.0446	-
1.1922	8850	0.0471	-
1.1990	8900	0.0516	-
1.2057	8950	0.0493	-
1.2124	9000	0.0482	0.0374
1.2192	9050	0.0442	-
1.2259	9100	0.0441	-
1.2327	9150	0.0471	-
1.2394	9200	0.047	-
1.2461	9250	0.0445	-
1.2529	9300	0.0468	-
1.2596	9350	0.0493	-
1.2663	9400	0.0453	-
1.2731	9450	0.0478	-
1.2798	9500	0.0417	0.0352
1.2865	9550	0.0452	-
1.2933	9600	0.0438	-
1.3000	9650	0.0419	-
1.3067	9700	0.0499	-
1.3135	9750	0.0414	-
1.3202	9800	0.0429	-
1.3270	9850	0.0443	-
1.3337	9900	0.0403	-
1.3404	9950	0.0466	-
1.3472	10000	0.0439	0.0323
1.3539	10050	0.0469	-
1.3606	10100	0.0459	-
1.3674	10150	0.0441	-
1.3741	10200	0.0428	-
1.3808	10250	0.0396	-
1.3876	10300	0.0406	-
1.3943	10350	0.0433	-
1.4011	10400	0.0421	-
1.4078	10450	0.0438	-
1.4145	10500	0.041	0.0310
1.4213	10550	0.0406	-
1.4280	10600	0.0386	-
1.4347	10650	0.0453	-
1.4415	10700	0.0429	-
1.4482	10750	0.0421	-
1.4549	10800	0.0385	-
1.4617	10850	0.0442	-
1.4684	10900	0.0402	-
1.4751	10950	0.0416	-
1.4819	11000	0.0433	0.0311
1.4886	11050	0.0404	-
1.4954	11100	0.0424	-
1.5021	11150	0.0373	-
1.5088	11200	0.0432	-
1.5156	11250	0.0364	-
1.5223	11300	0.0414	-
1.5290	11350	0.0409	-
1.5358	11400	0.0397	-
1.5425	11450	0.0425	-
1.5492	11500	0.0407	0.0308
1.5560	11550	0.0388	-
1.5627	11600	0.0396	-
1.5694	11650	0.037	-
1.5762	11700	0.0422	-
1.5829	11750	0.0406	-
1.5897	11800	0.0428	-
1.5964	11850	0.0387	-
1.6031	11900	0.0398	-
1.6099	11950	0.0405	-
1.6166	12000	0.0352	0.0297
1.6233	12050	0.0418	-
1.6301	12100	0.0374	-
1.6368	12150	0.0393	-
1.6435	12200	0.037	-
1.6503	12250	0.0402	-
1.6570	12300	0.0358	-
1.6637	12350	0.0331	-
1.6705	12400	0.0413	-
1.6772	12450	0.0382	-
1.684	12500	0.0409	0.0257
1.6907	12550	0.0388	-
1.6974	12600	0.0348	-
1.7042	12650	0.0345	-
1.7109	12700	0.0338	-
1.7176	12750	0.041	-
1.7244	12800	0.0369	-
1.7311	12850	0.0354	-
1.7378	12900	0.0384	-
1.7446	12950	0.0362	-
1.7513	13000	0.0336	0.0273
1.7580	13050	0.038	-
1.7648	13100	0.0387	-
1.7715	13150	0.0399	-
1.7783	13200	0.0355	-
1.7850	13250	0.0368	-
1.7917	13300	0.037	-
1.7985	13350	0.0347	-
1.8052	13400	0.0331	-
1.8119	13450	0.0362	-
1.8187	13500	0.0378	0.0258

The bold row denotes the saved checkpoint.

Framework Versions

Python: 3.10.12
Sentence Transformers: 5.2.0
Transformers: 4.57.3
PyTorch: 2.9.1+cu128
Accelerate: 1.12.0
Datasets: 4.4.2
Tokenizers: 0.22.1

Citation

BibTeX

Sentence Transformers

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}