---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-news_sentiment-analysis
  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. -->

# distilbert-news_sentiment-analysis

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co./distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2976
- Accuracy: 0.9264
- F1: 0.9264

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.3239        | 1.0   | 782  | 0.2484          | 0.9178   | 0.9179 |
| 0.1759        | 2.0   | 1564 | 0.2245          | 0.9268   | 0.9267 |
| 0.1218        | 3.0   | 2346 | 0.2377          | 0.9280   | 0.9280 |
| 0.0831        | 4.0   | 3128 | 0.2778          | 0.9289   | 0.9289 |
| 0.0605        | 5.0   | 3910 | 0.2976          | 0.9264   | 0.9264 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1