---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: tmvar_0.0001_0404_ES6_strict_tok1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# tmvar_0.0001_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: 0.1472
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9561

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
| 0.3183        | 0.49  | 25   | 0.2344          | 0.0       | 0.0    | 0.0 | 0.9555   |
| 0.232         | 0.98  | 50   | 0.2467          | 0.0       | 0.0    | 0.0 | 0.9555   |
| 0.2357        | 1.47  | 75   | 0.2341          | 0.0       | 0.0    | 0.0 | 0.9555   |
| 0.2245        | 1.96  | 100  | 0.2373          | 0.0       | 0.0    | 0.0 | 0.9555   |
| 0.1778        | 2.45  | 125  | 0.1339          | 0.0       | 0.0    | 0.0 | 0.9555   |
| 0.137         | 2.94  | 150  | 0.1222          | 0.0       | 0.0    | 0.0 | 0.9582   |
| 0.1146        | 3.43  | 175  | 0.1339          | 0.0       | 0.0    | 0.0 | 0.9625   |
| 0.1215        | 3.92  | 200  | 0.1472          | 0.0       | 0.0    | 0.0 | 0.9561   |


### Framework versions

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