distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5596
- Accuracy: 0.7714
- F1: 0.7538
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: 4e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.6146 | 1.0 | 31 | 0.5816 | 0.6857 | 0.6333 |
0.4054 | 2.0 | 62 | 0.5038 | 0.7643 | 0.7626 |
0.2892 | 3.0 | 93 | 0.5269 | 0.7714 | 0.7612 |
0.1895 | 4.0 | 124 | 0.5596 | 0.7714 | 0.7538 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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