---
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: fine_tuned_cb_bert
  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. -->

# fine_tuned_cb_bert

This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.2169
- Accuracy: 0.3636
- F1: 0.2430

## 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
- training_steps: 400

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| 0.7239        | 3.5714  | 50   | 1.2945          | 0.3182   | 0.1536 |
| 0.3879        | 7.1429  | 100  | 1.6236          | 0.4545   | 0.4158 |
| 0.1546        | 10.7143 | 150  | 3.1975          | 0.3636   | 0.2430 |
| 0.0741        | 14.2857 | 200  | 2.9703          | 0.4545   | 0.3895 |
| 0.0323        | 17.8571 | 250  | 3.8104          | 0.3636   | 0.2430 |
| 0.0073        | 21.4286 | 300  | 4.0583          | 0.3636   | 0.2430 |
| 0.0037        | 25.0    | 350  | 4.3166          | 0.3636   | 0.2430 |
| 0.0032        | 28.5714 | 400  | 4.2169          | 0.3636   | 0.2430 |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1