---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-sentiment
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-base-uncased-finetuned-sentiment

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: 0.3113
- Accuracy: 0.9288
- F1: 0.9288

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.2745        | 1.0   | 625  | 0.2015          | 0.9216   | 0.9215 |
| 0.1544        | 2.0   | 1250 | 0.1911          | 0.9264   | 0.9264 |
| 0.0957        | 3.0   | 1875 | 0.2519          | 0.9232   | 0.9232 |
| 0.0555        | 4.0   | 2500 | 0.2895          | 0.9288   | 0.9288 |
| 0.0356        | 5.0   | 3125 | 0.3113          | 0.9288   | 0.9288 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2