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: 0.2104
- Accuracy: 0.927
- F1: 0.9271
Model description
Labels description:
LABEL_0 = sadness
LABEL_1 = joy
LABEL_2 = love
LABEL_3 = anger
LABEL_4 = fear
LABEL_5 = 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 |
|---|---|---|---|---|---|
| 0.8179 | 1.0 | 250 | 0.3085 | 0.9085 | 0.9061 |
| 0.2431 | 2.0 | 500 | 0.2104 | 0.927 | 0.9271 |
Framework versions
- Transformers 4.16.2
- Pytorch 2.2.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.2
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Dataset used to train FaceHugger69420/distilbert-base-uncased-finetuned-emotion
Evaluation results
- Accuracy on emotionself-reported0.927
- F1 on emotionself-reported0.927