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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: 0.2144
- Accuracy: 0.9335
- F1: 0.9336
Model description
label0 = sadness label1 = joy label2 = love label3 = anger label4 = fear label5 = surprise
eg: model("I am extremely mesmerised")
output : [{'label': 'LABEL_5', 'score': 0.857551097869873}]
label5 = surprise
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 |
|---|---|---|---|---|---|
| 0.0275 | 1.0 | 250 | 0.2920 | 0.9355 | 0.9359 |
| 0.072 | 2.0 | 500 | 0.2144 | 0.9335 | 0.9336 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
