distilbert-base-uncased-finetuned-emotion
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: 0.2254
- Accuracy: 0.9275
- F1: 0.9274
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 with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.8569 | 1.0 | 250 | 0.3278 | 0.9075 | 0.9073 |
0.2571 | 2.0 | 500 | 0.2254 | 0.9275 | 0.9274 |
Framework versions
- Transformers 4.48.1
- Pytorch 2.7.0.dev20250127+cu126
- Tokenizers 0.21.0
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Model tree for mamgain93/distilbert-base-uncased-finetuned-emotion
Base model
distilbert/distilbert-base-uncased