Add new CrossEncoder model

README.md

@@ -0,0 +1,422 @@
+---
+language:
+- en
+tags:
+- sentence-transformers
+- cross-encoder
+- reranker
+- generated_from_trainer
+- dataset_size:5749
+- loss:BinaryCrossEntropyLoss
+base_model: distilbert/distilroberta-base
+datasets:
+- sentence-transformers/stsb
+pipeline_tag: text-ranking
+library_name: sentence-transformers
+metrics:
+- pearson
+- spearman
+model-index:
+- name: CrossEncoder based on distilbert/distilroberta-base
+  results:
+  - task:
+      type: cross-encoder-correlation
+      name: Cross Encoder Correlation
+    dataset:
+      name: stsb validation
+      type: stsb-validation
+    metrics:
+    - type: pearson
+      value: 0.8864227817727027
+      name: Pearson
+    - type: spearman
+      value: 0.8837678149208236
+      name: Spearman
+  - task:
+      type: cross-encoder-correlation
+      name: Cross Encoder Correlation
+    dataset:
+      name: stsb test
+      type: stsb-test
+    metrics:
+    - type: pearson
+      value: 0.8503521391700528
+      name: Pearson
+    - type: spearman
+      value: 0.8403655772346184
+      name: Spearman
+---
+
+# CrossEncoder based on distilbert/distilroberta-base
+
+This is a [Cross Encoder](https://www.sbert.net/docs/cross_encoder/usage/usage.html) model finetuned from [distilbert/distilroberta-base](https://huggingface.co/distilbert/distilroberta-base) on the [stsb](https://huggingface.co/datasets/sentence-transformers/stsb) dataset 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:** [distilbert/distilroberta-base](https://huggingface.co/distilbert/distilroberta-base) <!-- at revision fb53ab8802853c8e4fbdbcd0529f21fc6f459b2b -->
+- **Maximum Sequence Length:** 512 tokens
+- **Number of Output Labels:** 1 label
+- **Supported Modality:** Text
+- **Training Dataset:**
+    - [stsb](https://huggingface.co/datasets/sentence-transformers/stsb)
+- **Language:** en
+<!-- - **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/huggingface/sentence-transformers)
+- **Hugging Face:** [Cross Encoders on Hugging Face](https://huggingface.co/models?library=sentence-transformers&other=cross-encoder)
+
+### Full Model Architecture
+
+```
+CrossEncoder(
+  (0): Transformer({'transformer_task': 'sequence-classification', 'modality_config': {'text': {'method': 'forward', 'method_output_name': 'logits'}}, 'module_output_name': 'scores', 'architecture': 'RobertaForSequenceClassification'})
+)
+```
+
+## 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("omkar334/reranker-distilroberta-base-stsb")
+# Get scores for pairs of inputs
+pairs = [
+    ['A man with a hard hat is dancing.', 'A man wearing a hard hat is dancing.'],
+    ['A young child is riding a horse.', 'A child is riding a horse.'],
+    ['A man is feeding a mouse to a snake.', 'The man is feeding a mouse to the snake.'],
+    ['A woman is playing the guitar.', 'A man is playing guitar.'],
+    ['A woman is playing the flute.', 'A man is playing a flute.'],
+]
+scores = model.predict(pairs)
+print(scores)
+# [0.9598 0.9533 0.9566 0.3766 0.4535]
+
+# Or rank different texts based on similarity to a single text
+ranks = model.rank(
+    'A man with a hard hat is dancing.',
+    [
+        'A man wearing a hard hat is dancing.',
+        'A child is riding a horse.',
+        'The man is feeding a mouse to the snake.',
+        'A man is playing guitar.',
+        'A man is playing a flute.',
+    ]
+)
+# [{'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 Correlation
+
+* Datasets: `stsb-validation` and `stsb-test`
+* Evaluated with [<code>CrossEncoderCorrelationEvaluator</code>](https://sbert.net/docs/package_reference/cross_encoder/evaluation.html#sentence_transformers.cross_encoder.evaluation.CrossEncoderCorrelationEvaluator)
+
+| Metric       | stsb-validation | stsb-test  |
+|:-------------|:----------------|:-----------|
+| pearson      | 0.8864          | 0.8504     |
+| **spearman** | **0.8838**      | **0.8404** |
+
+<!--
+## 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
+
+#### stsb
+
+* Dataset: [stsb](https://huggingface.co/datasets/sentence-transformers/stsb) at [ab7a5ac](https://huggingface.co/datasets/sentence-transformers/stsb/tree/ab7a5ac0e35aa22088bdcf23e7fd99b220e53308)
+* Size: 5,749 training samples
+* Columns: <code>sentence1</code>, <code>sentence2</code>, and <code>score</code>
+* Approximate statistics based on the first 100 samples:
+  |          | sentence1                                                                        | sentence2                                                                        | score                                                          |
+  |:---------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------|
+  | type     | string                                                                           | string                                                                           | float                                                          |
+  | modality | text                                                                             | text                                                                             |                                                                |
+  | details  | <ul><li>min: 7 tokens</li><li>mean: 9.49 tokens</li><li>max: 14 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 9.61 tokens</li><li>max: 17 tokens</li></ul> | <ul><li>min: 0.1</li><li>mean: 0.66</li><li>max: 1.0</li></ul> |
+* Samples:
+  | sentence1                                                  | sentence2                                                             | score             |
+  |:-----------------------------------------------------------|:----------------------------------------------------------------------|:------------------|
+  | <code>A plane is taking off.</code>                        | <code>An air plane is taking off.</code>                              | <code>1.0</code>  |
+  | <code>A man is playing a large flute.</code>               | <code>A man is playing a flute.</code>                                | <code>0.76</code> |
+  | <code>A man is spreading shreded cheese on a pizza.</code> | <code>A man is spreading shredded cheese on an uncooked pizza.</code> | <code>0.76</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
+  }
+  ```
+
+### Evaluation Dataset
+
+#### stsb
+
+* Dataset: [stsb](https://huggingface.co/datasets/sentence-transformers/stsb) at [ab7a5ac](https://huggingface.co/datasets/sentence-transformers/stsb/tree/ab7a5ac0e35aa22088bdcf23e7fd99b220e53308)
+* Size: 1,500 evaluation samples
+* Columns: <code>sentence1</code>, <code>sentence2</code>, and <code>score</code>
+* Approximate statistics based on the first 100 samples:
+  |          | sentence1                                                                         | sentence2                                                                        | score                                                          |
+  |:---------|:----------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------|
+  | type     | string                                                                            | string                                                                           | float                                                          |
+  | modality | text                                                                              | text                                                                             |                                                                |
+  | details  | <ul><li>min: 7 tokens</li><li>mean: 10.04 tokens</li><li>max: 19 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 9.98 tokens</li><li>max: 18 tokens</li></ul> | <ul><li>min: 0.0</li><li>mean: 0.53</li><li>max: 1.0</li></ul> |
+* Samples:
+  | sentence1                                         | sentence2                                             | score             |
+  |:--------------------------------------------------|:------------------------------------------------------|:------------------|
+  | <code>A man with a hard hat is dancing.</code>    | <code>A man wearing a hard hat is dancing.</code>     | <code>1.0</code>  |
+  | <code>A young child is riding a horse.</code>     | <code>A child is riding a horse.</code>               | <code>0.95</code> |
+  | <code>A man is feeding a mouse to a snake.</code> | <code>The man is feeding a mouse to the snake.</code> | <code>1.0</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
+
+- `per_device_train_batch_size`: 64
+- `num_train_epochs`: 4
+- `warmup_steps`: 0.1
+- `bf16`: True
+- `per_device_eval_batch_size`: 64
+
+#### All Hyperparameters
+<details><summary>Click to expand</summary>
+
+- `per_device_train_batch_size`: 64
+- `num_train_epochs`: 4
+- `max_steps`: -1
+- `learning_rate`: 5e-05
+- `lr_scheduler_type`: linear
+- `lr_scheduler_kwargs`: None
+- `warmup_steps`: 0.1
+- `optim`: adamw_torch_fused
+- `optim_args`: None
+- `weight_decay`: 0.0
+- `adam_beta1`: 0.9
+- `adam_beta2`: 0.999
+- `adam_epsilon`: 1e-08
+- `optim_target_modules`: None
+- `gradient_accumulation_steps`: 1
+- `average_tokens_across_devices`: True
+- `max_grad_norm`: 1.0
+- `label_smoothing_factor`: 0.0
+- `bf16`: True
+- `fp16`: False
+- `bf16_full_eval`: False
+- `fp16_full_eval`: False
+- `tf32`: None
+- `gradient_checkpointing`: False
+- `gradient_checkpointing_kwargs`: None
+- `torch_compile`: False
+- `torch_compile_backend`: None
+- `torch_compile_mode`: None
+- `use_liger_kernel`: False
+- `liger_kernel_config`: None
+- `use_cache`: False
+- `neftune_noise_alpha`: None
+- `torch_empty_cache_steps`: None
+- `auto_find_batch_size`: False
+- `log_on_each_node`: True
+- `logging_nan_inf_filter`: True
+- `include_num_input_tokens_seen`: no
+- `log_level`: passive
+- `log_level_replica`: warning
+- `disable_tqdm`: False
+- `project`: huggingface
+- `trackio_space_id`: None
+- `trackio_bucket_id`: None
+- `trackio_static_space_id`: None
+- `per_device_eval_batch_size`: 64
+- `prediction_loss_only`: True
+- `eval_on_start`: False
+- `eval_do_concat_batches`: True
+- `eval_use_gather_object`: False
+- `eval_accumulation_steps`: None
+- `include_for_metrics`: []
+- `batch_eval_metrics`: False
+- `save_only_model`: False
+- `save_on_each_node`: False
+- `enable_jit_checkpoint`: False
+- `push_to_hub`: False
+- `hub_private_repo`: None
+- `hub_model_id`: None
+- `hub_strategy`: every_save
+- `hub_always_push`: False
+- `hub_revision`: None
+- `load_best_model_at_end`: False
+- `ignore_data_skip`: False
+- `restore_callback_states_from_checkpoint`: False
+- `full_determinism`: False
+- `seed`: 42
+- `data_seed`: None
+- `use_cpu`: False
+- `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
+- `dataloader_drop_last`: False
+- `dataloader_num_workers`: 0
+- `dataloader_pin_memory`: True
+- `dataloader_persistent_workers`: False
+- `dataloader_prefetch_factor`: None
+- `remove_unused_columns`: True
+- `label_names`: None
+- `train_sampling_strategy`: random
+- `length_column_name`: length
+- `ddp_find_unused_parameters`: None
+- `ddp_bucket_cap_mb`: None
+- `ddp_broadcast_buffers`: False
+- `ddp_static_graph`: None
+- `ddp_backend`: None
+- `ddp_timeout`: 1800
+- `fsdp`: []
+- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
+- `deepspeed`: None
+- `debug`: []
+- `skip_memory_metrics`: True
+- `do_predict`: False
+- `resume_from_checkpoint`: None
+- `warmup_ratio`: None
+- `local_rank`: -1
+- `prompts`: None
+- `batch_sampler`: batch_sampler
+- `multi_dataset_batch_sampler`: proportional
+- `router_mapping`: {}
+- `learning_rate_mapping`: {}
+
+</details>
+
+### Training Logs
+| Epoch  | Step | Training Loss | Validation Loss | stsb-validation_spearman | stsb-test_spearman |
+|:------:|:----:|:-------------:|:---------------:|:------------------------:|:------------------:|
+| -1     | -1   | -             | -               | -0.0362                  | -                  |
+| 0.2222 | 20   | 0.6909        | -               | -                        | -                  |
+| 0.4444 | 40   | 0.6506        | -               | -                        | -                  |
+| 0.6667 | 60   | 0.5969        | -               | -                        | -                  |
+| 0.8889 | 80   | 0.5680        | 0.5461          | 0.8552                   | -                  |
+| 1.1111 | 100  | 0.5551        | -               | -                        | -                  |
+| 1.3333 | 120  | 0.5379        | -               | -                        | -                  |
+| 1.5556 | 140  | 0.5449        | -               | -                        | -                  |
+| 1.7778 | 160  | 0.5443        | 0.5342          | 0.8777                   | -                  |
+| 2.0    | 180  | 0.5373        | -               | -                        | -                  |
+| 2.2222 | 200  | 0.5287        | -               | -                        | -                  |
+| 2.4444 | 220  | 0.5248        | -               | -                        | -                  |
+| 2.6667 | 240  | 0.5283        | 0.5383          | 0.8785                   | -                  |
+| 2.8889 | 260  | 0.5251        | -               | -                        | -                  |
+| 3.1111 | 280  | 0.5156        | -               | -                        | -                  |
+| 3.3333 | 300  | 0.5093        | -               | -                        | -                  |
+| 3.5556 | 320  | 0.5164        | 0.5369          | 0.8824                   | -                  |
+| 3.7778 | 340  | 0.5152        | -               | -                        | -                  |
+| 4.0    | 360  | 0.5208        | 0.5331          | 0.8838                   | -                  |
+| -1     | -1   | -             | -               | -                        | 0.8404             |
+
+
+### Training Time
+- **Training**: 3.2 minutes
+- **Evaluation**: 15.8 seconds
+- **Total**: 3.5 minutes
+
+### Framework Versions
+- Python: 3.11.14
+- Sentence Transformers: 5.6.0.dev0
+- Transformers: 5.9.0
+- PyTorch: 2.12.0
+- Accelerate: 1.13.0
+- Datasets: 4.8.5
+- Tokenizers: 0.22.2
+
+## Additional Resources
+
+- [Training and Finetuning Reranker Models with Sentence Transformers](https://huggingface.co/blog/train-reranker): the end-to-end guide for training or finetuning Cross Encoder (reranker) models.
+- [Multimodal Embedding & Reranker Models with Sentence Transformers](https://huggingface.co/blog/multimodal-sentence-transformers): use text, image, audio, and video reranker models through the same API.
+- [Training and Finetuning Multimodal Embedding & Reranker Models with Sentence Transformers](https://huggingface.co/blog/train-multimodal-sentence-transformers): training multimodal Cross Encoders.
+
+## 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 @@
+{
+  "add_cross_attention": false,
+  "architectures": [
+    "RobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "dtype": "float32",
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "LABEL_0"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "is_decoder": false,
+  "label2id": {
+    "LABEL_0": 0
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 6,
+  "pad_token_id": 1,
+  "tie_word_embeddings": true,
+  "transformers_version": "5.9.0",
+  "type_vocab_size": 1,
+  "use_cache": false,
+  "vocab_size": 50265
+}

config_sentence_transformers.json

@@ -0,0 +1,11 @@
+{
+  "__version__": {
+    "pytorch": "2.12.0",
+    "sentence_transformers": "5.6.0.dev0",
+    "transformers": "5.9.0"
+  },
+  "activation_fn": "torch.nn.modules.activation.Sigmoid",
+  "default_prompt_name": null,
+  "model_type": "CrossEncoder",
+  "prompts": {}
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:152992935bcc15111eecfd28af9a8b2af0831869026d056cb7dc4ba4cb33db4b
+size 328489204

modules.json

@@ -0,0 +1,8 @@
+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.base.modules.transformer.Transformer"
+  }
+]

sentence_bert_config.json

@@ -0,0 +1,10 @@
+{
+    "transformer_task": "sequence-classification",
+    "modality_config": {
+        "text": {
+            "method": "forward",
+            "method_output_name": "logits"
+        }
+    },
+    "module_output_name": "scores"
+}

tokenizer_config.json

@@ -0,0 +1,17 @@
+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": "<s>",
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "errors": "replace",
+  "is_local": false,
+  "local_files_only": false,
+  "mask_token": "<mask>",
+  "model_max_length": 512,
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "tokenizer_class": "RobertaTokenizer",
+  "trim_offsets": true,
+  "unk_token": "<unk>"
+}