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

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/thaisonatk/Fine-tune/runs/sibqe48b)
# check

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: 0.3991
- Accuracy: 0.8258

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6863        | 1.0   | 613  | 0.6746          | 0.6165   |
| 0.5276        | 2.0   | 1226 | 0.4910          | 0.7723   |
| 0.4828        | 3.0   | 1839 | 0.4693          | 0.7847   |
| 0.4682        | 4.0   | 2452 | 0.4413          | 0.8038   |
| 0.4692        | 5.0   | 3065 | 0.4330          | 0.8071   |
| 0.4387        | 6.0   | 3678 | 0.4344          | 0.8055   |
| 0.428         | 7.0   | 4291 | 0.4109          | 0.8191   |
| 0.4266        | 8.0   | 4904 | 0.4069          | 0.8208   |
| 0.4191        | 9.0   | 5517 | 0.4031          | 0.8233   |
| 0.434         | 10.0  | 6130 | 0.3991          | 0.8258   |


### Framework versions

- PEFT 0.10.0
- Transformers 4.41.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1