---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: bert-base-uncased_peft
  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-uncased_peft

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5427
- Accuracy: 0.8739

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9899        | 1.39  | 500  | 0.8556          | 0.7993   |
| 0.6821        | 2.78  | 1000 | 0.6157          | 0.8544   |
| 0.4306        | 4.17  | 1500 | 0.5656          | 0.8578   |
| 0.2885        | 5.56  | 2000 | 0.5595          | 0.8711   |
| 0.2203        | 6.94  | 2500 | 0.6113          | 0.8815   |
| 0.1599        | 8.33  | 3000 | 0.6234          | 0.8765   |
| 0.1223        | 9.72  | 3500 | 0.6867          | 0.8726   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.0