movie_classification_model
This model is a fine-tuned version of distilbert-base-uncased on the rotten_tomatoes dataset. It achieves the following results on the evaluation set:
- Loss: 0.4371
- Accuracy: 0.8518
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.3548 | 1.0 | 534 | 0.3769 | 0.8433 |
0.2349 | 2.0 | 1068 | 0.4371 | 0.8518 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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Model tree for Shibhani/movie_classification_model
Base model
distilbert/distilbert-base-uncased
Finetuned
this model
Dataset used to train Shibhani/movie_classification_model
Evaluation results
- Accuracy on rotten_tomatoestest set self-reported0.852