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nbbert

Token Classification
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bert
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  1. README.md +88 -0
  2. config.json +46 -0
  3. model.safetensors +3 -0
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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: cc-by-4.0
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+ base_model: NbAiLab/nb-bert-base
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: nbbert
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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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+ # nbbert
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+
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+ This model is a fine-tuned version of [NbAiLab/nb-bert-base](https://huggingface.co/NbAiLab/nb-bert-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Accuracy: 0.9305
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+ - Precision: 0.9342
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+ - Recall: 0.9305
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+ - F1: 0.9305
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+ - Loss: 0.4443
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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: 5e-05
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 8
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 20
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Accuracy | Precision | Recall | F1 | Validation Loss |
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+ |:-------------:|:-------:|:----:|:--------:|:---------:|:------:|:------:|:---------------:|
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+ | No log | 0.9412 | 8 | 0.4361 | 0.6823 | 0.4361 | 0.3171 | 0.8924 |
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+ | No log | 2.0 | 17 | 0.8851 | 0.8758 | 0.8851 | 0.8748 | 0.4652 |
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+ | No log | 2.9412 | 25 | 0.8281 | 0.8333 | 0.8281 | 0.8204 | 0.5819 |
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+ | No log | 4.0 | 34 | 0.8759 | 0.8922 | 0.8759 | 0.8749 | 0.4312 |
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+ | No log | 4.9412 | 42 | 0.8550 | 0.8762 | 0.8550 | 0.8548 | 0.5312 |
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+ | No log | 6.0 | 51 | 0.8944 | 0.8940 | 0.8944 | 0.8941 | 0.3318 |
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+ | No log | 6.9412 | 59 | 0.9209 | 0.9255 | 0.9209 | 0.9210 | 0.3824 |
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+ | No log | 8.0 | 68 | 0.9213 | 0.9282 | 0.9213 | 0.9219 | 0.4385 |
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+ | No log | 8.9412 | 76 | 0.9205 | 0.9226 | 0.9205 | 0.9205 | 0.3830 |
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+ | No log | 10.0 | 85 | 0.9249 | 0.9309 | 0.9249 | 0.9252 | 0.4137 |
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+ | No log | 10.9412 | 93 | 0.9269 | 0.9310 | 0.9269 | 0.9270 | 0.4014 |
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+ | No log | 12.0 | 102 | 0.9293 | 0.9321 | 0.9293 | 0.9293 | 0.3923 |
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+ | No log | 12.9412 | 110 | 0.9277 | 0.9320 | 0.9277 | 0.9278 | 0.4565 |
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+ | No log | 14.0 | 119 | 0.9305 | 0.9342 | 0.9305 | 0.9305 | 0.4166 |
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+ | No log | 14.9412 | 127 | 0.9281 | 0.9325 | 0.9281 | 0.9282 | 0.4512 |
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+ | No log | 16.0 | 136 | 0.9297 | 0.9336 | 0.9297 | 0.9298 | 0.4465 |
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+ | No log | 16.9412 | 144 | 0.9273 | 0.9318 | 0.9273 | 0.9274 | 0.4624 |
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+ | No log | 18.0 | 153 | 0.9277 | 0.9321 | 0.9277 | 0.9278 | 0.4593 |
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+ | No log | 18.8235 | 160 | 0.9305 | 0.9342 | 0.9305 | 0.9305 | 0.4443 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.4.1+cu121
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+ - Datasets 3.0.2
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+ - Tokenizers 0.19.1
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+ "BertForTokenClassification"
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+ ],
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+ "gradient_checkpointing": false,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "LABEL_0",
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 0,
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+ "pooler_fc_size": 768,
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+ "pooler_num_attention_heads": 12,
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+ "pooler_num_fc_layers": 3,
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+ "pooler_size_per_head": 128,
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+ "pooler_type": "first_token_transform",
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