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--- |
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library_name: transformers |
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base_model: allenai/scibert_scivocab_cased |
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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: scibert-finetuned-ner-dmdd |
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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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# scibert-finetuned-ner-dmdd |
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This model is a fine-tuned version of [allenai/scibert_scivocab_cased](https://huggingface.co/allenai/scibert_scivocab_cased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0121 |
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- Precision: 0.9717 |
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- Recall: 0.9820 |
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- F1: 0.9768 |
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- Accuracy: 0.9968 |
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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: 64 |
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- eval_batch_size: 64 |
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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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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.03 | 1.0 | 3803 | 0.0152 | 0.9536 | 0.9754 | 0.9644 | 0.9954 | |
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| 0.0182 | 2.0 | 7606 | 0.0115 | 0.9664 | 0.9805 | 0.9734 | 0.9965 | |
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| 0.0018 | 3.0 | 11409 | 0.0121 | 0.9717 | 0.9820 | 0.9768 | 0.9968 | |
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### Framework versions |
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- Transformers 4.51.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
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