---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: intent_classfication2
  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. -->

# intent_classfication2

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: 0.1321
- Accuracy: 0.9618

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6215        | 1.0   | 655  | 1.0384          | 0.8342   |
| 1.0518        | 2.0   | 1310 | 0.5333          | 0.8892   |
| 0.676         | 3.0   | 1965 | 0.3383          | 0.9228   |
| 0.3837        | 4.0   | 2620 | 0.2589          | 0.9373   |
| 0.3307        | 5.0   | 3275 | 0.2148          | 0.9415   |
| 0.2926        | 6.0   | 3930 | 0.1872          | 0.9492   |
| 0.2465        | 7.0   | 4585 | 0.1698          | 0.9530   |
| 0.2338        | 8.0   | 5240 | 0.1585          | 0.9553   |
| 0.2156        | 9.0   | 5895 | 0.1486          | 0.9599   |
| 0.2078        | 10.0  | 6550 | 0.1429          | 0.9603   |
| 0.2           | 11.0  | 7205 | 0.1392          | 0.9603   |
| 0.1973        | 12.0  | 7860 | 0.1362          | 0.9614   |
| 0.184         | 13.0  | 8515 | 0.1339          | 0.9622   |
| 0.1884        | 14.0  | 9170 | 0.1326          | 0.9622   |
| 0.1871        | 15.0  | 9825 | 0.1321          | 0.9618   |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0