---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: tmvar_5e-05_0404_ES6_strict_tok1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# tmvar_5e-05_0404_ES6_strict_tok1

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.
It achieves the following results on the evaluation set:
- Loss: 0.0372
- Precision: 0.7742
- Recall: 0.8528
- F1: 0.8116
- Accuracy: 0.9906

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 2000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.3642        | 0.49  | 25   | 0.0757          | 0.0       | 0.0    | 0.0    | 0.9727   |
| 0.0672        | 0.98  | 50   | 0.0660          | 0.6397    | 0.4416 | 0.5225 | 0.9841   |
| 0.0347        | 1.47  | 75   | 0.0357          | 0.7129    | 0.7310 | 0.7218 | 0.9888   |
| 0.0292        | 1.96  | 100  | 0.0255          | 0.7630    | 0.8173 | 0.7892 | 0.9903   |
| 0.012         | 2.45  | 125  | 0.0325          | 0.6923    | 0.8223 | 0.7517 | 0.9903   |
| 0.0087        | 2.94  | 150  | 0.0372          | 0.7742    | 0.8528 | 0.8116 | 0.9906   |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3