---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned_bert_sentiment_classification
  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. -->

# finetuned_bert_sentiment_classification

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9785
- Accuracy: 0.78

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 68   | 0.6297          | 0.73     |
| No log        | 2.0   | 136  | 0.9044          | 0.73     |
| No log        | 3.0   | 204  | 1.2008          | 0.78     |
| No log        | 4.0   | 272  | 1.4143          | 0.75     |
| No log        | 5.0   | 340  | 1.4934          | 0.76     |
| No log        | 6.0   | 408  | 1.5581          | 0.765    |
| No log        | 7.0   | 476  | 1.6158          | 0.78     |
| 0.1371        | 8.0   | 544  | 1.6786          | 0.785    |
| 0.1371        | 9.0   | 612  | 1.7112          | 0.78     |
| 0.1371        | 10.0  | 680  | 1.7416          | 0.78     |
| 0.1371        | 11.0  | 748  | 1.7667          | 0.78     |
| 0.1371        | 12.0  | 816  | 1.7937          | 0.78     |
| 0.1371        | 13.0  | 884  | 1.8139          | 0.78     |
| 0.1371        | 14.0  | 952  | 1.8347          | 0.78     |
| 0.0002        | 15.0  | 1020 | 1.8531          | 0.785    |
| 0.0002        | 16.0  | 1088 | 1.8645          | 0.78     |
| 0.0002        | 17.0  | 1156 | 1.8798          | 0.78     |
| 0.0002        | 18.0  | 1224 | 1.8964          | 0.78     |
| 0.0002        | 19.0  | 1292 | 1.9097          | 0.78     |
| 0.0002        | 20.0  | 1360 | 1.9206          | 0.78     |
| 0.0002        | 21.0  | 1428 | 1.9310          | 0.78     |
| 0.0002        | 22.0  | 1496 | 1.9410          | 0.78     |
| 0.0001        | 23.0  | 1564 | 1.9494          | 0.78     |
| 0.0001        | 24.0  | 1632 | 1.9566          | 0.78     |
| 0.0001        | 25.0  | 1700 | 1.9628          | 0.78     |
| 0.0001        | 26.0  | 1768 | 1.9681          | 0.78     |
| 0.0001        | 27.0  | 1836 | 1.9730          | 0.78     |
| 0.0001        | 28.0  | 1904 | 1.9761          | 0.78     |
| 0.0001        | 29.0  | 1972 | 1.9779          | 0.78     |
| 0.0           | 30.0  | 2040 | 1.9785          | 0.78     |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0