---
license: apache-2.0
base_model: google-bert/bert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: BERT-base
  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

This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6524
- Accuracy: 0.4265

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 22   | 1.8763          | 0.2549   |
| No log        | 2.0   | 44   | 1.8652          | 0.25     |
| No log        | 3.0   | 66   | 1.7901          | 0.3088   |
| No log        | 4.0   | 88   | 1.7617          | 0.3235   |
| No log        | 5.0   | 110  | 1.7064          | 0.3676   |
| No log        | 6.0   | 132  | 1.6792          | 0.4167   |
| No log        | 7.0   | 154  | 1.6574          | 0.4216   |
| No log        | 8.0   | 176  | 1.6524          | 0.4265   |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0+cpu
- Datasets 2.21.0
- Tokenizers 0.19.1