Add new CrossEncoder model

README.md

@@ -0,0 +1,385 @@
+---
+tags:
+- sentence-transformers
+- cross-encoder
+- generated_from_trainer
+- dataset_size:12128
+- loss:BinaryCrossEntropyLoss
+base_model: yoriis/ce-tydi
+pipeline_tag: text-ranking
+library_name: sentence-transformers
+metrics:
+- accuracy
+- accuracy_threshold
+- f1
+- f1_threshold
+- precision
+- recall
+- average_precision
+model-index:
+- name: CrossEncoder based on yoriis/ce-tydi
+  results:
+  - task:
+      type: cross-encoder-classification
+      name: Cross Encoder Classification
+    dataset:
+      name: eval
+      type: eval
+    metrics:
+    - type: accuracy
+      value: 0.9347181008902077
+      name: Accuracy
+    - type: accuracy_threshold
+      value: 0.641675591468811
+      name: Accuracy Threshold
+    - type: f1
+      value: 0.8668639053254438
+      name: F1
+    - type: f1_threshold
+      value: 0.303142249584198
+      name: F1 Threshold
+    - type: precision
+      value: 0.8643067846607669
+      name: Precision
+    - type: recall
+      value: 0.8694362017804155
+      name: Recall
+    - type: average_precision
+      value: 0.9277836243055002
+      name: Average Precision
+---
+
+# CrossEncoder based on yoriis/ce-tydi
+
+This is a [Cross Encoder](https://www.sbert.net/docs/cross_encoder/usage/usage.html) model finetuned from [yoriis/ce-tydi](https://huggingface.co/yoriis/ce-tydi) using the [sentence-transformers](https://www.SBERT.net) 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:** [yoriis/ce-tydi](https://huggingface.co/yoriis/ce-tydi) <!-- at revision adbd5e3122de4b21a7cd3fc2e5f7fa1aed62b1ee -->
+- **Maximum Sequence Length:** 512 tokens
+- **Number of Output Labels:** 1 label
+<!-- - **Training Dataset:** Unknown -->
+<!-- - **Language:** Unknown -->
+<!-- - **License:** Unknown -->
+
+### Model Sources
+
+- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
+- **Documentation:** [Cross Encoder Documentation](https://www.sbert.net/docs/cross_encoder/usage/usage.html)
+- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
+- **Hugging Face:** [Cross Encoders on Hugging Face](https://huggingface.co/models?library=sentence-transformers&other=cross-encoder)
+
+## Usage
+
+### Direct Usage (Sentence Transformers)
+
+First install the Sentence Transformers library:
+
+```bash
+pip install -U sentence-transformers
+```
+
+Then you can load this model and run inference.
+```python
+from sentence_transformers import CrossEncoder
+
+# Download from the 🤗 Hub
+model = CrossEncoder("yoriis/ce-tydi-quqa")
+# Get scores for pairs of texts
+pairs = [
+    ['ما وقت حلول صاعقة العذاب بقوم لوط\xa0عليه السلام؟', 'قل إنما حرم ربي الفواحش ما ظهر منها وما بطن والإثم والبغي بغير الحق وأن تشركوا بالله ما لم ينزل به سلطانا وأن تقولوا على الله ما لا تعلمون{33}الأعراف.'],
+    ['ما أول دعاء في القرآن ؟', 'كذلك يوحي إليك وإلى الذين من قبلك الله العزيز الحكيم {3}الشورى'],
+    ['ما هي شروط قبول التوبة؟', 'إن الذين يكفرون بالله ورسله ويريدون أن يفرقوا بين الله ورسله ويقولون نؤمن ببعض ونكفر ببعض ويريدون أن يتخذوا بين ذلك سبيلا{150} أولـئك هم الكافرون حقا وأعتدنا للكافرين عذابا مهينا{151} النساء.'],
+    ['ما هي شروط شهادة لا إله الا الله، وأن محمدا رسول الله ؟', 'ثم تولوا عنه وقالوا معلم مجنون{14} الدخان'],
+    ['ما هي اسماء المدن المذكورة في القرآن؟', 'فلولا كانت قرية آمنت فنفعها إيمانها إلا قوم يونس لما آمنوا كشفنا عنهم عذاب الخزي في الحياة الدنيا ومتعناهم إلى حين{98} يونس'],
+]
+scores = model.predict(pairs)
+print(scores.shape)
+# (5,)
+
+# Or rank different texts based on similarity to a single text
+ranks = model.rank(
+    'ما وقت حلول صاعقة العذاب بقوم لوط\xa0عليه السلام؟',
+    [
+        'قل إنما حرم ربي الفواحش ما ظهر منها وما بطن والإثم والبغي بغير الحق وأن تشركوا بالله ما لم ينزل به سلطانا وأن تقولوا على الله ما لا تعلمون{33}الأعراف.',
+        'كذلك يوحي إليك وإلى الذين من قبلك الله العزيز الحكيم {3}الشورى',
+        'إن الذين يكفرون بالله ورسله ويريدون أن يفرقوا بين الله ورسله ويقولون نؤمن ببعض ونكفر ببعض ويريدون أن يتخذوا بين ذلك سبيلا{150} أولـئك هم الكافرون حقا وأعتدنا للكافرين عذابا مهينا{151} النساء.',
+        'ثم تولوا عنه وقالوا معلم مجنون{14} الدخان',
+        'فلولا كانت قرية آمنت فنفعها إيمانها إلا قوم يونس لما آمنوا كشفنا عنهم عذاب الخزي في الحياة الدنيا ومتعناهم إلى حين{98} يونس',
+    ]
+)
+# [{'corpus_id': ..., 'score': ...}, {'corpus_id': ..., 'score': ...}, ...]
+```
+
+<!--
+### Direct Usage (Transformers)
+
+<details><summary>Click to see the direct usage in Transformers</summary>
+
+</details>
+-->
+
+<!--
+### Downstream Usage (Sentence Transformers)
+
+You can finetune this model on your own dataset.
+
+<details><summary>Click to expand</summary>
+
+</details>
+-->
+
+<!--
+### Out-of-Scope Use
+
+*List how the model may foreseeably be misused and address what users ought not to do with the model.*
+-->
+
+## Evaluation
+
+### Metrics
+
+#### Cross Encoder Classification
+
+* Dataset: `eval`
+* Evaluated with [<code>CrossEncoderClassificationEvaluator</code>](https://sbert.net/docs/package_reference/cross_encoder/evaluation.html#sentence_transformers.cross_encoder.evaluation.CrossEncoderClassificationEvaluator)
+
+| Metric                | Value      |
+|:----------------------|:-----------|
+| accuracy              | 0.9347     |
+| accuracy_threshold    | 0.6417     |
+| f1                    | 0.8669     |
+| f1_threshold          | 0.3031     |
+| precision             | 0.8643     |
+| recall                | 0.8694     |
+| **average_precision** | **0.9278** |
+
+<!--
+## Bias, Risks and Limitations
+
+*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
+-->
+
+<!--
+### Recommendations
+
+*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
+-->
+
+## Training Details
+
+### Training Dataset
+
+#### Unnamed Dataset
+
+* Size: 12,128 training samples
+* Columns: <code>sentence_0</code>, <code>sentence_1</code>, and <code>label</code>
+* Approximate statistics based on the first 1000 samples:
+  |         | sentence_0                                                                                     | sentence_1                                                                                        | label                                                          |
+  |:--------|:-----------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------|:---------------------------------------------------------------|
+  | type    | string                                                                                         | string                                                                                            | float                                                          |
+  | details | <ul><li>min: 9 characters</li><li>mean: 74.83 characters</li><li>max: 659 characters</li></ul> | <ul><li>min: 15 characters</li><li>mean: 130.39 characters</li><li>max: 1279 characters</li></ul> | <ul><li>min: 0.0</li><li>mean: 0.27</li><li>max: 1.0</li></ul> |
+* Samples:
+  | sentence_0                                                  | sentence_1                                                                                                                                                                                                   | label            |
+  |:------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------|
+  | <code>ما وقت حلول صاعقة العذاب بقوم لوط عليه السلام؟</code> | <code>قل إنما حرم ربي الفواحش ما ظهر منها وما بطن والإثم والبغي بغير الحق وأن تشركوا بالله ما لم ينزل به سلطانا وأن تقولوا على الله ما لا تعلمون{33}الأعراف.</code>                                          | <code>0.0</code> |
+  | <code>ما أول دعاء في القرآن ؟</code>                        | <code>كذلك يوحي إليك وإلى الذين من قبلك الله العزيز الحكيم {3}الشورى</code>                                                                                                                                  | <code>0.0</code> |
+  | <code>ما هي شروط قبول التوبة؟</code>                        | <code>إن الذين يكفرون بالله ورسله ويريدون أن يفرقوا بين الله ورسله ويقولون نؤمن ببعض ونكفر ببعض ويريدون أن يتخذوا بين ذلك سبيلا{150} أولـئك هم الكافرون حقا وأعتدنا للكافرين عذابا مهينا{151} النساء.</code> | <code>0.0</code> |
+* Loss: [<code>BinaryCrossEntropyLoss</code>](https://sbert.net/docs/package_reference/cross_encoder/losses.html#binarycrossentropyloss) with these parameters:
+  ```json
+  {
+      "activation_fn": "torch.nn.modules.linear.Identity",
+      "pos_weight": null
+  }
+  ```
+
+### Training Hyperparameters
+#### Non-Default Hyperparameters
+
+- `eval_strategy`: steps
+- `per_device_train_batch_size`: 16
+- `per_device_eval_batch_size`: 16
+- `num_train_epochs`: 4
+- `fp16`: True
+
+#### All Hyperparameters
+<details><summary>Click to expand</summary>
+
+- `overwrite_output_dir`: False
+- `do_predict`: False
+- `eval_strategy`: steps
+- `prediction_loss_only`: True
+- `per_device_train_batch_size`: 16
+- `per_device_eval_batch_size`: 16
+- `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`: 5e-05
+- `weight_decay`: 0.0
+- `adam_beta1`: 0.9
+- `adam_beta2`: 0.999
+- `adam_epsilon`: 1e-08
+- `max_grad_norm`: 1
+- `num_train_epochs`: 4
+- `max_steps`: -1
+- `lr_scheduler_type`: linear
+- `lr_scheduler_kwargs`: {}
+- `warmup_ratio`: 0.0
+- `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
+- `use_ipex`: False
+- `bf16`: False
+- `fp16`: True
+- `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`: 0
+- `dataloader_prefetch_factor`: None
+- `past_index`: -1
+- `disable_tqdm`: False
+- `remove_unused_columns`: True
+- `label_names`: None
+- `load_best_model_at_end`: False
+- `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}
+- `deepspeed`: None
+- `label_smoothing_factor`: 0.0
+- `optim`: adamw_torch
+- `optim_args`: None
+- `adafactor`: False
+- `group_by_length`: False
+- `length_column_name`: length
+- `ddp_find_unused_parameters`: None
+- `ddp_bucket_cap_mb`: None
+- `ddp_broadcast_buffers`: False
+- `dataloader_pin_memory`: True
+- `dataloader_persistent_workers`: False
+- `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`: False
+- `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`: False
+- `prompts`: None
+- `batch_sampler`: batch_sampler
+- `multi_dataset_batch_sampler`: proportional
+
+</details>
+
+### Training Logs
+| Epoch  | Step | Training Loss | eval_average_precision |
+|:------:|:----:|:-------------:|:----------------------:|
+| 0.6596 | 500  | 0.3554        | 0.8973                 |
+| 1.0    | 758  | -             | 0.9116                 |
+| 1.3193 | 1000 | 0.2635        | 0.9163                 |
+| 1.9789 | 1500 | 0.2561        | 0.9224                 |
+| 2.0    | 1516 | -             | 0.9227                 |
+| 2.6385 | 2000 | 0.2284        | 0.9248                 |
+| 3.0    | 2274 | -             | 0.9270                 |
+| 3.2982 | 2500 | 0.2316        | 0.9275                 |
+| 3.9578 | 3000 | 0.2068        | 0.9278                 |
+| 4.0    | 3032 | -             | 0.9278                 |
+
+
+### Framework Versions
+- Python: 3.11.13
+- Sentence Transformers: 4.1.0
+- Transformers: 4.54.0
+- PyTorch: 2.6.0+cu124
+- Accelerate: 1.9.0
+- Datasets: 4.0.0
+- Tokenizers: 0.21.2
+
+## Citation
+
+### BibTeX
+
+#### Sentence Transformers
+```bibtex
+@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",
+}
+```
+
+<!--
+## Glossary
+
+*Clearly define terms in order to be accessible across audiences.*
+-->
+
+<!--
+## Model Card Authors
+
+*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
+-->
+
+<!--
+## Model Card Contact
+
+*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
+-->

config.json

@@ -0,0 +1,34 @@
+{
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "LABEL_0"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "LABEL_0": 0
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "sentence_transformers": {
+    "activation_fn": "torch.nn.modules.activation.Sigmoid",
+    "version": "4.1.0"
+  },
+  "torch_dtype": "float32",
+  "transformers_version": "4.54.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 64000
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:23f0942abc5f46f29baceacc92142939117c29176b6319110775a67846d8ff8b
+size 540799996

special_tokens_map.json

@@ -0,0 +1,37 @@
+{
+  "cls_token": {
+    "content": "[CLS]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "[MASK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "[PAD]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "[SEP]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

@@ -0,0 +1,94 @@
+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "3": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "4": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "5": {
+      "content": "[رابط]",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": true,
+      "special": true
+    },
+    "6": {
+      "content": "[بريد]",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": true,
+      "special": true
+    },
+    "7": {
+      "content": "[مستخدم]",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": true,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": false,
+  "extra_special_tokens": {},
+  "mask_token": "[MASK]",
+  "max_len": 512,
+  "max_length": 512,
+  "model_max_length": 512,
+  "never_split": [
+    "[بريد]",
+    "[مستخدم]",
+    "[رابط]"
+  ],
+  "pad_to_multiple_of": null,
+  "pad_token": "[PAD]",
+  "pad_token_type_id": 0,
+  "padding_side": "right",
+  "sep_token": "[SEP]",
+  "stride": 0,
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "[UNK]"
+}