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--- |
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library_name: transformers |
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license: mit |
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base_model: FacebookAI/roberta-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: RoBERTa-Base-full-finetuned-ner-multi-label |
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results: [] |
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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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# RoBERTa-Base-full-finetuned-ner-multi-label |
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This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0484 |
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- F1 Micro: 0.8025 |
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- Precision Micro: 0.8296 |
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- Recall Micro: 0.7772 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 Micro | Precision Micro | Recall Micro | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:| |
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| No log | 1.0 | 27 | 0.1227 | 0.6758 | 0.7555 | 0.6114 | |
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| No log | 2.0 | 54 | 0.0750 | 0.7087 | 0.9323 | 0.5716 | |
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| No log | 3.0 | 81 | 0.0628 | 0.7597 | 0.8531 | 0.6848 | |
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| No log | 4.0 | 108 | 0.0554 | 0.7868 | 0.8768 | 0.7136 | |
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| No log | 5.0 | 135 | 0.0522 | 0.7987 | 0.8228 | 0.7759 | |
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| No log | 6.0 | 162 | 0.0508 | 0.7967 | 0.8283 | 0.7674 | |
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| No log | 7.0 | 189 | 0.0493 | 0.8005 | 0.8263 | 0.7763 | |
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| No log | 8.0 | 216 | 0.0489 | 0.8032 | 0.8253 | 0.7822 | |
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| No log | 9.0 | 243 | 0.0490 | 0.8014 | 0.8171 | 0.7864 | |
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| No log | 10.0 | 270 | 0.0484 | 0.8025 | 0.8296 | 0.7772 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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