distilbert-base-uncased-finetuned-emotion1
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: 0.1681
- Accuracy: 0.9315
- F1: 0.9319
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
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.8164 | 1.0 | 250 | 0.2985 | 0.91 | 0.9084 |
0.2216 | 2.0 | 500 | 0.1871 | 0.9235 | 0.9234 |
0.1481 | 3.0 | 750 | 0.1681 | 0.9315 | 0.9319 |
Framework versions
- Transformers 4.16.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1
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