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: 0.2186
- Accuracy: 0.924
- F1: 0.9241
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 |
|---|---|---|---|---|---|
| 0.8218 | 1.0 | 250 | 0.3165 | 0.9025 | 0.9001 |
| 0.2494 | 2.0 | 500 | 0.2186 | 0.924 | 0.9241 |
Framework versions
- Transformers 4.19.4
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
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Dataset used to train andreaschandra/distilbert-base-uncased-finetuned-emotion
Evaluation results
- Accuracy on emotionself-reported0.924
- F1 on emotionself-reported0.924