---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased-finetuned-sst-2-english
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: imdb
  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

This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2032
- Accuracy: 0.927
- Precision: 0.9241
- Recall: 0.9318
- F1: 0.9280

## 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-06
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.2612        | 1.0   | 625  | 0.2290          | 0.9122   | 0.9080    | 0.9191 | 0.9135 |
| 0.218         | 2.0   | 1250 | 0.2174          | 0.919    | 0.9114    | 0.9298 | 0.9205 |
| 0.2019        | 3.0   | 1875 | 0.2120          | 0.922    | 0.9197    | 0.9263 | 0.9230 |
| 0.1806        | 4.0   | 2500 | 0.2070          | 0.9214   | 0.9122    | 0.9342 | 0.9230 |
| 0.1711        | 5.0   | 3125 | 0.2052          | 0.9244   | 0.9191    | 0.9322 | 0.9256 |
| 0.1605        | 6.0   | 3750 | 0.2032          | 0.9236   | 0.9164    | 0.9338 | 0.9250 |
| 0.1639        | 7.0   | 4375 | 0.2062          | 0.9244   | 0.9152    | 0.9370 | 0.9260 |
| 0.1544        | 8.0   | 5000 | 0.2026          | 0.9268   | 0.9265    | 0.9287 | 0.9276 |
| 0.148         | 9.0   | 5625 | 0.2035          | 0.9274   | 0.9212    | 0.9362 | 0.9286 |
| 0.144         | 10.0  | 6250 | 0.2032          | 0.927    | 0.9241    | 0.9318 | 0.9280 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1