emotion-classifier-distilbert-lora
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2179
- F1 Macro: 0.1433
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Macro |
|---|---|---|---|---|
| 0.2775 | 1.0 | 1307 | 0.2532 | 0.0016 |
| 0.2346 | 2.0 | 2614 | 0.2272 | 0.0821 |
| 0.2256 | 3.0 | 3921 | 0.2198 | 0.1369 |
| 0.2224 | 4.0 | 5228 | 0.2179 | 0.1433 |
Framework versions
- PEFT 0.14.0
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
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Model tree for Ludwigd/emotion-classifier-distilbert-lora
Base model
distilbert/distilbert-base-uncased