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: 0.2143
- Accuracy: 0.923
- F1: 0.9231
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 |
|---|---|---|---|---|---|
| 0.8258 | 1.0 | 250 | 0.2989 | 0.9115 | 0.9098 |
| 0.242 | 2.0 | 500 | 0.2143 | 0.923 | 0.9231 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.13.1+cu117
- Datasets 2.9.0
- Tokenizers 0.10.3
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Model tree for smallsuper/distilbert-base-uncased-finetuned-emotion
Base model
distilbert/distilbert-base-uncasedDataset used to train smallsuper/distilbert-base-uncased-finetuned-emotion
Evaluation results
- Accuracy on emotionself-reported0.923
- F1 on emotionself-reported0.923