metadata
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: distilbert-base-uncased-imdb
results: []
language:
- en
library_name: transformers
pipeline_tag: text-classification
distilbert-base-uncased-imdb
This model is a fine-tuned version of distilbert/distilbert-base-uncased on Imdb Movie Reviews Sentiment Analysis (Kaggle) dataset. It achieves the following results on the evaluation set:
- Loss: 0.2898
- Accuracy: 0.9284
- Precision: 0.9281
- Recall: 0.9288
- F1: 0.9284
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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.2727 | 1.0 | 625 | 0.2194 | 0.9178 | 0.8853 | 0.96 | 0.9211 |
| 0.1569 | 2.0 | 1250 | 0.2082 | 0.9236 | 0.8957 | 0.9588 | 0.9262 |
| 0.1211 | 3.0 | 1875 | 0.2739 | 0.9256 | 0.9379 | 0.9116 | 0.9245 |
| 0.0544 | 4.0 | 2500 | 0.2898 | 0.9284 | 0.9281 | 0.9288 | 0.9284 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1