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: 0.2190
- Accuracy: 0.9235
- F1: 0.9234
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: 2
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
Accuracy |
F1 |
| 0.7995 |
1.0 |
250 |
0.3161 |
0.9045 |
0.9017 |
| 0.254 |
2.0 |
500 |
0.2190 |
0.9235 |
0.9234 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.2.2
- Datasets 2.16.0
- Tokenizers 0.13.3
