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README.md
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---
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license: mit
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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: Yepes_0.0001_250
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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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# Yepes_0.0001_250
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This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1555
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- Precision: 0.5922
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- Recall: 0.4552
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- F1: 0.5148
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- Accuracy: 0.9768
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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: 0.0001
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- train_batch_size: 16
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- eval_batch_size: 16
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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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- training_steps: 500
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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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| 0.4065 | 1.39 | 25 | 0.2115 | 0.0 | 0.0 | 0.0 | 0.9672 |
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| 0.1995 | 2.78 | 50 | 0.2120 | 0.0 | 0.0 | 0.0 | 0.9672 |
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| 0.1995 | 4.17 | 75 | 0.2108 | 0.0 | 0.0 | 0.0 | 0.9672 |
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| 0.1694 | 5.56 | 100 | 0.1646 | 0.0 | 0.0 | 0.0 | 0.9672 |
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| 0.1493 | 6.94 | 125 | 0.1513 | 0.0 | 0.0 | 0.0 | 0.9672 |
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| 0.1266 | 8.33 | 150 | 0.1446 | 0.0 | 0.0 | 0.0 | 0.9672 |
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| 0.106 | 9.72 | 175 | 0.1396 | 0.4019 | 0.2139 | 0.2792 | 0.9704 |
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| 0.086 | 11.11 | 200 | 0.1162 | 0.5037 | 0.3408 | 0.4065 | 0.9740 |
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| 0.0613 | 12.5 | 225 | 0.1230 | 0.5015 | 0.4104 | 0.4514 | 0.9740 |
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| 0.047 | 13.89 | 250 | 0.1306 | 0.5333 | 0.4378 | 0.4809 | 0.9753 |
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| 0.0351 | 15.28 | 275 | 0.1351 | 0.5629 | 0.4453 | 0.4972 | 0.9757 |
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| 0.0266 | 16.67 | 300 | 0.1453 | 0.5617 | 0.4303 | 0.4873 | 0.9765 |
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| 0.02 | 18.06 | 325 | 0.1441 | 0.5573 | 0.4478 | 0.4966 | 0.9757 |
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| 0.0153 | 19.44 | 350 | 0.1555 | 0.5922 | 0.4552 | 0.5148 | 0.9768 |
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### Framework versions
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- Transformers 4.27.4
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- Pytorch 1.13.1+cu116
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- Datasets 2.11.0
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- Tokenizers 0.13.2
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