---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: bert-base-uncased-finetuned-stationary-epoch-update
  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. -->

# bert-base-uncased-finetuned-stationary-epoch-update

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: 1.0945
- Accuracy: 0.8167
- F1: 0.8090

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.6008        | 1.0   | 38   | 0.5006          | 0.7267   | 0.6924 |
| 0.4314        | 2.0   | 76   | 0.4429          | 0.81     | 0.8107 |
| 0.3104        | 3.0   | 114  | 0.4770          | 0.8067   | 0.8005 |
| 0.1893        | 4.0   | 152  | 0.6433          | 0.81     | 0.7985 |
| 0.1103        | 5.0   | 190  | 0.7405          | 0.8      | 0.7841 |
| 0.0708        | 6.0   | 228  | 0.7971          | 0.8133   | 0.8025 |
| 0.0464        | 7.0   | 266  | 0.9670          | 0.79     | 0.7727 |
| 0.0224        | 8.0   | 304  | 1.0068          | 0.8067   | 0.7964 |
| 0.0163        | 9.0   | 342  | 0.9835          | 0.8033   | 0.7959 |
| 0.0182        | 10.0  | 380  | 1.0203          | 0.8067   | 0.7981 |
| 0.0118        | 11.0  | 418  | 1.0874          | 0.8133   | 0.8034 |
| 0.0052        | 12.0  | 456  | 1.1500          | 0.81     | 0.7985 |
| 0.0052        | 13.0  | 494  | 1.0991          | 0.8167   | 0.8082 |
| 0.0076        | 14.0  | 532  | 1.1015          | 0.82     | 0.8104 |
| 0.0037        | 15.0  | 570  | 1.0945          | 0.8167   | 0.8090 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0