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: 0.1507
- Accuracy: 0.9335
- F1: 0.9336
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.1737 | 1.0 | 250 | 0.1817 | 0.931 | 0.9320 |
| 0.1136 | 2.0 | 500 | 0.1629 | 0.9305 | 0.9312 |
| 0.0985 | 3.0 | 750 | 0.1507 | 0.9335 | 0.9336 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.1
- Tokenizers 0.13.3
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Model tree for OmarEmam99/distilbert-base-uncased-finetuned-emotion
Base model
distilbert/distilbert-base-uncasedDataset used to train OmarEmam99/distilbert-base-uncased-finetuned-emotion
Evaluation results
- Accuracy on emotionvalidation set self-reported0.933
- F1 on emotionvalidation set self-reported0.934