license: apache-2.0 base_model: distilbert-base-uncased tags:
- generated_from_trainer datasets:
- stanfordnlp/imdb metrics:
- perplexity model-index:
- name: test-distilbert-base-uncased-finetuned-imdb results: - task: name: Masked Language Modeling type: fill-mask dataset: name: imdb type: kde4 args: fill-mask metrics: - name: perplexity type: perplexity value: 12.05
distilbert-base-uncased-finetuned-imdb
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.4894
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.6819 | 1.0 | 157 | 2.4978 |
| 2.5872 | 2.0 | 314 | 2.4488 |
| 2.527 | 3.0 | 471 | 2.4823 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1