metadata
library_name: transformers
license: apache-2.0
base_model: hwting/distilbert-base-uncased-finetuned-imdb
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: fintuned-distilbert-imdb-classification
results: []
fintuned-distilbert-imdb-classification
This model is a fine-tuned version of hwting/distilbert-base-uncased-finetuned-imdb on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2013
- Accuracy: 0.9298
- F1: 0.9302
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.2433 | 1.0 | 391 | 0.2010 | 0.9218 | 0.9201 |
| 0.1644 | 2.0 | 782 | 0.1867 | 0.9312 | 0.9311 |
| 0.1117 | 3.0 | 1173 | 0.2013 | 0.9298 | 0.9302 |
Framework versions
- Transformers 5.8.0
- Pytorch 2.11.0+cu130
- Datasets 4.8.5
- Tokenizers 0.22.2