---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: BERT_finetune_sentiment
  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_finetune_sentiment

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8911

## 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.3369        | 1.0   | 625   | 0.2635          |
| 0.1885        | 2.0   | 1250  | 0.4271          |
| 0.1329        | 3.0   | 1875  | 0.5429          |
| 0.0545        | 4.0   | 2500  | 0.5134          |
| 0.0313        | 5.0   | 3125  | 0.6778          |
| 0.0275        | 6.0   | 3750  | 0.7123          |
| 0.0276        | 7.0   | 4375  | 0.6549          |
| 0.021         | 8.0   | 5000  | 0.6959          |
| 0.0153        | 9.0   | 5625  | 0.7736          |
| 0.0083        | 10.0  | 6250  | 0.7828          |
| 0.0111        | 11.0  | 6875  | 0.8629          |
| 0.0046        | 12.0  | 7500  | 0.8794          |
| 0.0091        | 13.0  | 8125  | 0.7696          |
| 0.0064        | 14.0  | 8750  | 0.8840          |
| 0.0035        | 15.0  | 9375  | 0.9002          |
| 0.0014        | 16.0  | 10000 | 0.9629          |
| 0.0049        | 17.0  | 10625 | 1.0240          |
| 0.0051        | 18.0  | 11250 | 0.9016          |
| 0.0021        | 19.0  | 11875 | 0.9011          |
| 0.0012        | 20.0  | 12500 | 0.8911          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1