Add new CrossEncoder model

README.md

@@ -0,0 +1,435 @@
+---
+language:
+- hu
+license: apache-2.0
+tags:
+- sentence-transformers
+- cross-encoder
+- reranker
+- generated_from_trainer
+- dataset_size:32113
+- loss:BinaryCrossEntropyLoss
+base_model: GaborMadarasz/ModernBERT-base-hungarian
+pipeline_tag: text-ranking
+library_name: sentence-transformers
+metrics:
+- map
+- mrr@10
+- ndcg@10
+model-index:
+- name: ModernBERT-base trained on Chemistry
+  results:
+  - task:
+      type: cross-encoder-reranking
+      name: Cross Encoder Reranking
+    dataset:
+      name: chem dev
+      type: chem-dev
+    metrics:
+    - type: map
+      value: 0.4646
+      name: Map
+    - type: mrr@10
+      value: 0.4614
+      name: Mrr@10
+    - type: ndcg@10
+      value: 0.4928
+      name: Ndcg@10
+---
+
+# ModernBERT-base trained on Chemistry
+
+This is a [Cross Encoder](https://www.sbert.net/docs/cross_encoder/usage/usage.html) model finetuned from [GaborMadarasz/ModernBERT-base-hungarian](https://huggingface.co/GaborMadarasz/ModernBERT-base-hungarian) 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:** [GaborMadarasz/ModernBERT-base-hungarian](https://huggingface.co/GaborMadarasz/ModernBERT-base-hungarian) <!-- at revision 32d70514a6587e31e23ff8ea3d0dc98bc61e42e4 -->
+- **Maximum Sequence Length:** 8192 tokens
+- **Number of Output Labels:** 1 label
+<!-- - **Training Dataset:** Unknown -->
+- **Language:** hu
+- **License:** apache-2.0
+
+### 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("GaborMadarasz/reranker-ModernBERT-base-hungarian")
+# Get scores for pairs of texts
+pairs = [
+    ['Milyen halmazállapotú a klór szobahőmérsékleten?', 'Gáz'],
+    ['Milyen halmazállapotú a klór szobahőmérsékleten?', 'Gáz.'],
+    ['Mi az izoméria fogalma?', 'Azonos összegképletű, de eltérő szerkezetű és tulajdonságú anyagok. '],
+    ['Melyik elektronhéjon található a hidrogénatom egyetlen elektronja?', 'Az első héjon.'],
+    ['Milyen felhasználási területei vannak a szilíciumnak?', 'Ötvözőelemként, tranzisztorok, integrált áramkörök, fényelemek előállítására.'],
+]
+scores = model.predict(pairs)
+print(scores.shape)
+# (5,)
+
+# Or rank different texts based on similarity to a single text
+ranks = model.rank(
+    'Milyen halmazállapotú a klór szobahőmérsékleten?',
+    [
+        'Gáz',
+        'Gáz.',
+        'Azonos összegképletű, de eltérő szerkezetű és tulajdonságú anyagok. ',
+        'Az első héjon.',
+        'Ötvözőelemként, tranzisztorok, integrált áramkörök, fényelemek előállítására.',
+    ]
+)
+# [{'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 Reranking
+
+* Dataset: `chem-dev`
+* Evaluated with [<code>CrossEncoderRerankingEvaluator</code>](https://sbert.net/docs/package_reference/cross_encoder/evaluation.html#sentence_transformers.cross_encoder.evaluation.CrossEncoderRerankingEvaluator) with these parameters:
+  ```json
+  {
+      "at_k": 10,
+      "always_rerank_positives": false
+  }
+  ```
+
+| Metric      | Value                |
+|:------------|:---------------------|
+| map         | 0.4646 (+0.0929)     |
+| mrr@10      | 0.4614 (+0.0966)     |
+| **ndcg@10** | **0.4928 (+0.0910)** |
+
+<!--
+## 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: 32,113 training samples
+* Columns: <code>query</code>, <code>answer</code>, and <code>label</code>
+* Approximate statistics based on the first 1000 samples:
+  |         | query                                                                                         | answer                                                                                         | label                                           |
+  |:--------|:----------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------------|:------------------------------------------------|
+  | type    | string                                                                                        | string                                                                                         | int                                             |
+  | details | <ul><li>min: 8 characters</li><li>mean: 52.3 characters</li><li>max: 159 characters</li></ul> | <ul><li>min: 1 characters</li><li>mean: 83.87 characters</li><li>max: 531 characters</li></ul> | <ul><li>0: ~69.80%</li><li>1: ~30.20%</li></ul> |
+* Samples:
+  | query                                                         | answer                                                                            | label          |
+  |:--------------------------------------------------------------|:----------------------------------------------------------------------------------|:---------------|
+  | <code>Milyen halmazállapotú a klór szobahőmérsékleten?</code> | <code>Gáz</code>                                                                  | <code>1</code> |
+  | <code>Milyen halmazállapotú a klór szobahőmérsékleten?</code> | <code>Gáz.</code>                                                                 | <code>1</code> |
+  | <code>Mi az izoméria fogalma?</code>                          | <code>Azonos összegképletű, de eltérő szerkezetű és tulajdonságú anyagok. </code> | <code>1</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": 5
+  }
+  ```
+
+### Training Hyperparameters
+#### Non-Default Hyperparameters
+
+- `eval_strategy`: steps
+- `per_device_train_batch_size`: 2
+- `per_device_eval_batch_size`: 2
+- `gradient_accumulation_steps`: 8
+- `learning_rate`: 2e-05
+- `warmup_ratio`: 0.1
+- `seed`: 12
+- `dataloader_num_workers`: 2
+- `load_best_model_at_end`: 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`: 2
+- `per_device_eval_batch_size`: 2
+- `per_gpu_train_batch_size`: None
+- `per_gpu_eval_batch_size`: None
+- `gradient_accumulation_steps`: 8
+- `eval_accumulation_steps`: None
+- `torch_empty_cache_steps`: None
+- `learning_rate`: 2e-05
+- `weight_decay`: 0.0
+- `adam_beta1`: 0.9
+- `adam_beta2`: 0.999
+- `adam_epsilon`: 1e-08
+- `max_grad_norm`: 1.0
+- `num_train_epochs`: 3
+- `max_steps`: -1
+- `lr_scheduler_type`: linear
+- `lr_scheduler_kwargs`: {}
+- `warmup_ratio`: 0.1
+- `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`: 12
+- `data_seed`: None
+- `jit_mode_eval`: False
+- `use_ipex`: False
+- `bf16`: False
+- `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`: 2
+- `dataloader_prefetch_factor`: None
+- `past_index`: -1
+- `disable_tqdm`: False
+- `remove_unused_columns`: True
+- `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}
+- `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
+- `router_mapping`: {}
+- `learning_rate_mapping`: {}
+
+</details>
+
+### Training Logs
+| Epoch      | Step     | Training Loss | chem-dev_ndcg@10     |
+|:----------:|:--------:|:-------------:|:--------------------:|
+| -1         | -1       | -             | 0.1188 (-0.2831)     |
+| 0.0005     | 1        | 1.9222        | -                    |
+| 0.0498     | 100      | 1.8084        | -                    |
+| 0.0996     | 200      | 1.2947        | 0.2862 (-0.1157)     |
+| 0.1495     | 300      | 1.1573        | -                    |
+| 0.1993     | 400      | 1.17          | 0.3567 (-0.0452)     |
+| 0.2491     | 500      | 1.0609        | -                    |
+| 0.2989     | 600      | 1.01          | 0.3747 (-0.0272)     |
+| 0.3488     | 700      | 0.9806        | -                    |
+| 0.3986     | 800      | 0.9208        | 0.3963 (-0.0056)     |
+| 0.4484     | 900      | 0.9022        | -                    |
+| 0.4982     | 1000     | 0.8722        | 0.4106 (+0.0087)     |
+| 0.5480     | 1100     | 0.9325        | -                    |
+| 0.5979     | 1200     | 0.768         | 0.4316 (+0.0298)     |
+| 0.6477     | 1300     | 0.8151        | -                    |
+| 0.6975     | 1400     | 0.7569        | 0.4506 (+0.0487)     |
+| 0.7473     | 1500     | 0.7216        | -                    |
+| 0.7972     | 1600     | 0.7571        | 0.4643 (+0.0625)     |
+| 0.8470     | 1700     | 0.6993        | -                    |
+| 0.8968     | 1800     | 0.6709        | 0.4713 (+0.0694)     |
+| 0.9466     | 1900     | 0.7021        | -                    |
+| 0.9965     | 2000     | 0.7693        | 0.4805 (+0.0787)     |
+| 1.0458     | 2100     | 0.5179        | -                    |
+| 1.0957     | 2200     | 0.4932        | 0.4800 (+0.0781)     |
+| 1.1455     | 2300     | 0.5568        | -                    |
+| 1.1953     | 2400     | 0.4191        | 0.4821 (+0.0803)     |
+| 1.2451     | 2500     | 0.4702        | -                    |
+| 1.2949     | 2600     | 0.4126        | 0.4851 (+0.0833)     |
+| 1.3448     | 2700     | 0.4744        | -                    |
+| 1.3946     | 2800     | 0.4404        | 0.4907 (+0.0888)     |
+| 1.4444     | 2900     | 0.4712        | -                    |
+| 1.4942     | 3000     | 0.4382        | 0.4913 (+0.0894)     |
+| 1.5441     | 3100     | 0.5049        | -                    |
+| 1.5939     | 3200     | 0.4714        | 0.4886 (+0.0868)     |
+| 1.6437     | 3300     | 0.3885        | -                    |
+| 1.6935     | 3400     | 0.4361        | 0.4924 (+0.0906)     |
+| 1.7434     | 3500     | 0.4207        | -                    |
+| **1.7932** | **3600** | **0.4384**    | **0.4928 (+0.0910)** |
+| 1.8430     | 3700     | 0.4187        | -                    |
+| 1.8928     | 3800     | 0.4271        | 0.4937 (+0.0919)     |
+| 1.9426     | 3900     | 0.3581        | -                    |
+| 1.9925     | 4000     | 0.3751        | 0.4910 (+0.0891)     |
+| 2.0419     | 4100     | 0.2494        | -                    |
+| 2.0917     | 4200     | 0.2045        | 0.4869 (+0.0850)     |
+| 2.1415     | 4300     | 0.1532        | -                    |
+| 2.1913     | 4400     | 0.1268        | 0.4838 (+0.0820)     |
+| 2.2411     | 4500     | 0.2108        | -                    |
+| 2.2910     | 4600     | 0.2292        | 0.4889 (+0.0870)     |
+| 2.3408     | 4700     | 0.2154        | -                    |
+| 2.3906     | 4800     | 0.1574        | 0.4921 (+0.0902)     |
+| 2.4404     | 4900     | 0.1677        | -                    |
+| 2.4903     | 5000     | 0.1596        | 0.4826 (+0.0807)     |
+| 2.5401     | 5100     | 0.1456        | -                    |
+| 2.5899     | 5200     | 0.2177        | 0.4867 (+0.0849)     |
+| 2.6397     | 5300     | 0.1227        | -                    |
+| 2.6895     | 5400     | 0.1638        | 0.4880 (+0.0862)     |
+| 2.7394     | 5500     | 0.1192        | -                    |
+| 2.7892     | 5600     | 0.2003        | 0.4848 (+0.0829)     |
+| 2.8390     | 5700     | 0.2717        | -                    |
+| 2.8888     | 5800     | 0.1546        | 0.4841 (+0.0822)     |
+| 2.9387     | 5900     | 0.268         | -                    |
+| 2.9885     | 6000     | 0.2253        | 0.4858 (+0.0840)     |
+| -1         | -1       | -             | 0.4928 (+0.0910)     |
+
+* The bold row denotes the saved checkpoint.
+
+### Framework Versions
+- Python: 3.10.12
+- Sentence Transformers: 5.0.0
+- Transformers: 4.53.2
+- PyTorch: 2.7.0+cpu
+- Accelerate: 1.6.0
+- Datasets: 3.2.0
+- 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 +1,55 @@
+{
+  "architectures": [
+    "ModernBertForSequenceClassification"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": null,
+  "classifier_activation": "gelu",
+  "classifier_bias": false,
+  "classifier_dropout": 0.0,
+  "classifier_pooling": "mean",
+  "cls_token_id": 50281,
+  "decoder_bias": true,
+  "deterministic_flash_attn": false,
+  "embedding_dropout": 0.0,
+  "eos_token_id": null,
+  "global_attn_every_n_layers": 3,
+  "global_rope_theta": 160000.0,
+  "gradient_checkpointing": false,
+  "hidden_activation": "gelu",
+  "hidden_size": 768,
+  "id2label": {
+    "0": "LABEL_0"
+  },
+  "initializer_cutoff_factor": 2.0,
+  "initializer_range": 0.02,
+  "intermediate_size": 1152,
+  "label2id": {
+    "LABEL_0": 0
+  },
+  "layer_norm_eps": 1e-05,
+  "local_attention": 128,
+  "local_rope_theta": 10000.0,
+  "max_position_embeddings": 8192,
+  "mlp_bias": false,
+  "mlp_dropout": 0.0,
+  "model_type": "modernbert",
+  "norm_bias": false,
+  "norm_eps": 1e-05,
+  "num_attention_heads": 12,
+  "num_hidden_layers": 22,
+  "pad_token_id": 50283,
+  "position_embedding_type": "absolute",
+  "repad_logits_with_grad": false,
+  "sentence_transformers": {
+    "activation_fn": "torch.nn.modules.activation.Sigmoid",
+    "version": "5.0.0"
+  },
+  "sep_token_id": 50282,
+  "sparse_pred_ignore_index": -100,
+  "sparse_prediction": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.53.2",
+  "vocab_size": 52000
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ebd8034784cd34d437731f89cb0c9a2e59b167a87220bc31fb703c0411dd55bd
+size 603450212

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": true,
+    "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 +1,73 @@
+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<|padding|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "3": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "4": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "5": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "6": {
+      "content": "[MASK]",
+      "lstrip": true,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "extra_special_tokens": {},
+  "mask_token": "[MASK]",
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 8192,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "tokenizer_class": "PreTrainedTokenizerFast",
+  "unk_token": "[UNK]"
+}