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distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of distilbert-base-uncased on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.1698
- Accuracy: 0.937
- F1: 0.9372
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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.1395 | 1.0 | 250 | 0.1659 | 0.9355 | 0.9358 |
0.0945 | 2.0 | 500 | 0.1657 | 0.935 | 0.9351 |
0.0783 | 3.0 | 750 | 0.1832 | 0.937 | 0.9371 |
0.0653 | 4.0 | 1000 | 0.1729 | 0.9335 | 0.9332 |
0.053 | 5.0 | 1250 | 0.1698 | 0.937 | 0.9372 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3