---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: imdb-distilbert-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. -->

# imdb-distilbert-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: 0.4325
- Accuracy: 0.8796
- Precision: 0.8725
- Recall: 0.8892
- F1: 0.8808

## 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: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.3175        | 1.0   | 1563 | 0.3278          | 0.8607   | 0.9120    | 0.7985 | 0.8515 |
| 0.2139        | 2.0   | 3126 | 0.3392          | 0.8773   | 0.8679    | 0.8901 | 0.8788 |
| 0.1325        | 3.0   | 4689 | 0.4325          | 0.8796   | 0.8725    | 0.8892 | 0.8808 |


### Framework versions

- Transformers 4.57.0
- Pytorch 2.5.1+cu121
- Datasets 4.1.1
- Tokenizers 0.22.1