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--- |
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library_name: transformers |
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base_model: allenai/biomed_roberta_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: BioMedRoBERTa-finetuned-ner-pablo-just-classifier |
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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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# BioMedRoBERTa-finetuned-ner-pablo-just-classifier |
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This model is a fine-tuned version of [allenai/biomed_roberta_base](https://huggingface.co/allenai/biomed_roberta_base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1276 |
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- Precision: 0.6818 |
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- Recall: 0.7031 |
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- F1: 0.6923 |
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- Accuracy: 0.9672 |
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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: 0.1 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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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: 0.05 |
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- num_epochs: 5 |
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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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| 0.7191 | 1.0 | 2509 | 0.5248 | 0.5127 | 0.6334 | 0.5667 | 0.9486 | |
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| 0.5382 | 2.0 | 5018 | 0.4280 | 0.5378 | 0.6500 | 0.5886 | 0.9556 | |
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| 0.3968 | 3.0 | 7527 | 0.3095 | 0.4997 | 0.6714 | 0.5730 | 0.9531 | |
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| 0.2528 | 4.0 | 10036 | 0.1872 | 0.5631 | 0.6850 | 0.6181 | 0.9599 | |
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| 0.1541 | 5.0 | 12545 | 0.1276 | 0.6818 | 0.7031 | 0.6923 | 0.9672 | |
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### Framework versions |
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- Transformers 4.44.1 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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