distilbert-deysi-dataset-finetuned-emotion
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0921
- Accuracy: 0.6653
- F1: 0.5828
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 |
|---|---|---|---|---|---|
| 1.743 | 1.0 | 38 | 1.2221 | 0.5943 | 0.4431 |
| 1.2644 | 2.0 | 76 | 1.0921 | 0.6653 | 0.5828 |
Framework versions
- Transformers 4.16.2
- Pytorch 2.2.1
- Datasets 2.17.1
- Tokenizers 0.15.2
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