---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_token_classification_14PTC_aug800_fixed
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# BERT_token_classification_14PTC_aug800_fixed

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5869
- Precision: 0.0559
- Recall: 0.0728
- F1: 0.0633
- Accuracy: 0.7101

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.6525        | 1.0   | 1839  | 1.1412          | 0.0228    | 0.0133 | 0.0168 | 0.7311   |
| 0.3649        | 2.0   | 3678  | 1.1856          | 0.0351    | 0.0302 | 0.0325 | 0.7211   |
| 0.2838        | 3.0   | 5517  | 1.2173          | 0.0650    | 0.0631 | 0.0640 | 0.7328   |
| 0.2152        | 4.0   | 7356  | 1.3204          | 0.0578    | 0.0631 | 0.0603 | 0.7231   |
| 0.1864        | 5.0   | 9195  | 1.3214          | 0.0594    | 0.0613 | 0.0603 | 0.7312   |
| 0.1579        | 6.0   | 11034 | 1.4035          | 0.0616    | 0.0577 | 0.0596 | 0.7220   |
| 0.1427        | 7.0   | 12873 | 1.4422          | 0.0529    | 0.0657 | 0.0586 | 0.7068   |
| 0.1297        | 8.0   | 14712 | 1.5468          | 0.0623    | 0.0835 | 0.0713 | 0.7059   |
| 0.1161        | 9.0   | 16551 | 1.5283          | 0.0621    | 0.0790 | 0.0696 | 0.7140   |
| 0.0943        | 10.0  | 18390 | 1.5869          | 0.0559    | 0.0728 | 0.0633 | 0.7101   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.13.3