<!-- 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: 0.1423
- Accuracy: 0.934
- F1: 0.9342
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 |
---|---|---|---|---|---|
0.7568 | 1.0 | 250 | 0.2651 | 0.912 | 0.9099 |
0.2008 | 2.0 | 500 | 0.1684 | 0.931 | 0.9316 |
0.1302 | 3.0 | 750 | 0.1556 | 0.933 | 0.9334 |
0.1046 | 4.0 | 1000 | 0.1466 | 0.933 | 0.9326 |
0.087 | 5.0 | 1250 | 0.1423 | 0.934 | 0.9342 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0+cu102
- Datasets 2.6.1
- Tokenizers 0.12.1