Token Classification
Transformers
Safetensors
French
modernbert
bourdoiscatie commited on
Commit
c870e03
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1 Parent(s): 50a2ef7

Training complete

Browse files
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: almanach/moderncamembert-cv2-base
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: moderncamembert-cv2-frenchNER_4entities
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # moderncamembert-cv2-frenchNER_4entities
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+
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+ This model is a fine-tuned version of [almanach/moderncamembert-cv2-base](https://huggingface.co/almanach/moderncamembert-cv2-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0722
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+ - Precision: 0.9829
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+ - Recall: 0.9829
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+ - F1: 0.9829
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+ - Accuracy: 0.9829
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 3
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:------:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.0349 | 1.0 | 41095 | 0.0549 | 0.9812 | 0.9812 | 0.9812 | 0.9812 |
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+ | 0.022 | 2.0 | 82190 | 0.0519 | 0.9835 | 0.9835 | 0.9835 | 0.9835 |
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+ | 0.0082 | 3.0 | 123285 | 0.0722 | 0.9829 | 0.9829 | 0.9829 | 0.9829 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.49.0
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+ - Pytorch 2.6.0+cu124
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+ - Datasets 3.3.2
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+ - Tokenizers 0.21.0
config.json ADDED
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+ {
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+ "_name_or_path": "almanach/moderncamembert-cv2-base",
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+ "architectures": [
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+ "ModernBertForTokenClassification"
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+ ],
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+ "attention_bias": false,
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+ "attention_dropout": 0.0,
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+ "bos_token_id": 1,
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+ "classifier_activation": "silu",
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+ "classifier_bias": false,
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+ "classifier_dropout": 0.0,
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+ "classifier_pooling": "mean",
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+ "cls_token_id": 1,
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+ "decoder_bias": true,
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+ "deterministic_flash_attn": false,
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+ "embedding_dropout": 0.0,
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+ "eos_token_id": 2,
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+ "global_attn_every_n_layers": 3,
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+ "global_rope_theta": 160000.0,
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+ "gradient_checkpointing": false,
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+ "hidden_activation": "gelu",
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "B-O",
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+ "1": "B-PER",
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+ "2": "B-ORG",
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+ "3": "B-LOC",
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+ "4": "B-MISC"
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+ },
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+ "initializer_cutoff_factor": 2.0,
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+ "initializer_range": 0.02,
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+ "B-LOC": 3,
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+ "B-MISC": 4,
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+ "B-PER": 1
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+ },
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+ "layer_norm_eps": 1e-05,
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+ "local_attention": 128,
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+ "local_rope_theta": 10000.0,
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+ "max_position_embeddings": 8192,
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+ "mlp_bias": false,
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+ "mlp_dropout": 0.0,
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+ "model_type": "modernbert",
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+ "norm_bias": false,
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+ "norm_eps": 1e-05,
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 22,
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+ "pad_token_id": 0,
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+ "position_embedding_type": "absolute",
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+ "reference_compile": true,
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+ "repad_logits_with_grad": false,
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+ "sep_token_id": 2,
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+ "sparse_pred_ignore_index": -100,
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+ "sparse_prediction": false,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.49.0",
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+ "vocab_size": 32768
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+ }
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tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
tokenizer_config.json ADDED
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