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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: 0.1382
- Accuracy: 0.941
- F1: 0.9411
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: 128
- eval_batch_size: 128
- 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 |
---|---|---|---|---|---|
0.1911 | 1.0 | 125 | 0.1728 | 0.9285 | 0.9290 |
0.1302 | 2.0 | 250 | 0.1500 | 0.9365 | 0.9364 |
0.1068 | 3.0 | 375 | 0.1451 | 0.9365 | 0.9367 |
0.0912 | 4.0 | 500 | 0.1391 | 0.939 | 0.9389 |
0.077 | 5.0 | 625 | 0.1382 | 0.941 | 0.9411 |
Framework versions
- Transformers 4.30.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3