finetuning-sentiment-model-1500-samples
This model is a fine-tuned version of distilbert-base-uncased on the imdb dataset. It achieves the following results on the evaluation set:
- Loss: 0.3496
- Accuracy: 0.87
- F1: 0.8721
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: 5e-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 | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 94 | 0.3214 | 0.8667 | 0.8649 |
| No log | 2.0 | 188 | 0.3496 | 0.87 | 0.8721 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.1.0
- Datasets 2.12.0
- Tokenizers 0.13.2
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Model tree for tonyla25/finetuning-sentiment-model-1500-samples
Base model
distilbert/distilbert-base-uncasedDataset used to train tonyla25/finetuning-sentiment-model-1500-samples
Evaluation results
- Accuracy on imdbtest set self-reported0.870
- F1 on imdbtest set self-reported0.872