<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
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: 0.1703
- Accuracy: 0.936
- F1: 0.9360
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: 6
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.1741 | 1.0 | 250 | 0.1757 | 0.93 | 0.9309 |
0.1158 | 2.0 | 500 | 0.1692 | 0.932 | 0.9330 |
0.1014 | 3.0 | 750 | 0.1848 | 0.9285 | 0.9290 |
0.0778 | 4.0 | 1000 | 0.1703 | 0.9395 | 0.9394 |
0.0616 | 5.0 | 1250 | 0.1672 | 0.938 | 0.9379 |
0.0534 | 6.0 | 1500 | 0.1703 | 0.936 | 0.9360 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1