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

# results

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: 1.0462
- Accuracy: 0.565

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 15
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.6966        | 0.12   | 30   | 1.6482          | 0.205    |
| 1.6111        | 0.24   | 60   | 1.5500          | 0.312    |
| 1.5634        | 0.36   | 90   | 1.4253          | 0.391    |
| 1.4389        | 0.48   | 120  | 1.2866          | 0.429    |
| 1.3507        | 0.6    | 150  | 1.2292          | 0.466    |
| 1.3072        | 0.72   | 180  | 1.2251          | 0.435    |
| 1.2346        | 0.84   | 210  | 1.3498          | 0.412    |
| 1.3884        | 0.96   | 240  | 1.1693          | 0.515    |
| 1.0748        | 1.08   | 270  | 1.2255          | 0.474    |
| 1.02          | 1.2    | 300  | 1.2691          | 0.475    |
| 1.0354        | 1.32   | 330  | 1.1937          | 0.48     |
| 1.0622        | 1.44   | 360  | 1.1304          | 0.512    |
| 1.0289        | 1.56   | 390  | 1.2823          | 0.465    |
| 1.1433        | 1.6800 | 420  | 1.0603          | 0.527    |
| 1.0125        | 1.8    | 450  | 1.0753          | 0.522    |
| 0.8716        | 1.92   | 480  | 1.0901          | 0.532    |
| 0.8761        | 2.04   | 510  | 1.0462          | 0.565    |
| 0.6857        | 2.16   | 540  | 1.0626          | 0.555    |
| 0.7674        | 2.2800 | 570  | 1.0799          | 0.545    |
| 0.6676        | 2.4    | 600  | 1.0843          | 0.546    |
| 0.6254        | 2.52   | 630  | 1.1148          | 0.551    |
| 0.6813        | 2.64   | 660  | 1.1227          | 0.553    |
| 0.7043        | 2.76   | 690  | 1.1267          | 0.558    |
| 0.4643        | 2.88   | 720  | 1.1227          | 0.551    |
| 0.6665        | 3.0    | 750  | 1.1222          | 0.557    |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1