metadata
library_name: transformers
language:
- en
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-sentiment
results: []
distilbert-base-uncased-finetuned-sentiment
This model is a fine-tuned version of distilbert-base-uncased on the imdb-dataset-of-50k-movie-reviews dataset. It achieves the following results on the evaluation set:
- Loss: 0.2047
- Accuracy: 0.9293
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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3001 | 1.0 | 1250 | 0.2115 | 0.9198 |
| 0.1616 | 2.0 | 2500 | 0.2047 | 0.9293 |
| 0.0968 | 3.0 | 3750 | 0.2511 | 0.9293 |
| 0.0558 | 4.0 | 5000 | 0.3152 | 0.928 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3