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--- |
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license: apache-2.0 |
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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: BERT_ep9_lr4 |
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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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# BERT_ep9_lr4 |
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This model is a fine-tuned version of [ajtamayoh/NER_EHR_Spanish_model_Mulitlingual_BERT](https://huggingface.co/ajtamayoh/NER_EHR_Spanish_model_Mulitlingual_BERT) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1801 |
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- Precision: 0.6659 |
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- Recall: 0.7266 |
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- F1: 0.6950 |
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- Accuracy: 0.9478 |
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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-08 |
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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: 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: 9 |
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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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| No log | 1.0 | 467 | 0.2732 | 0.6635 | 0.6619 | 0.6627 | 0.9415 | |
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| 0.2772 | 2.0 | 934 | 0.2436 | 0.6562 | 0.6820 | 0.6688 | 0.9426 | |
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| 0.2379 | 3.0 | 1401 | 0.2224 | 0.6550 | 0.6980 | 0.6758 | 0.9437 | |
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| 0.2142 | 4.0 | 1868 | 0.2071 | 0.6597 | 0.7104 | 0.6841 | 0.9450 | |
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| 0.1968 | 5.0 | 2335 | 0.1960 | 0.6597 | 0.7165 | 0.6869 | 0.9461 | |
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| 0.1888 | 6.0 | 2802 | 0.1884 | 0.6610 | 0.7195 | 0.6890 | 0.9468 | |
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| 0.1788 | 7.0 | 3269 | 0.1835 | 0.6641 | 0.7244 | 0.6929 | 0.9474 | |
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| 0.1768 | 8.0 | 3736 | 0.1808 | 0.6652 | 0.7258 | 0.6942 | 0.9477 | |
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| 0.1695 | 9.0 | 4203 | 0.1801 | 0.6659 | 0.7266 | 0.6950 | 0.9478 | |
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### Framework versions |
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- Transformers 4.27.4 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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