distilbert-finetuned-emotion-lora
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: 0.3782
- F1: 0.8359
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.6074 | 1.0 | 1000 | 0.5574 | 0.7503 |
| 0.4558 | 2.0 | 2000 | 0.4197 | 0.8072 |
| 0.4014 | 3.0 | 3000 | 0.3782 | 0.8359 |
Framework versions
- PEFT 0.17.1
- Transformers 4.57.0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
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Model tree for pyproln/distilbert-finetuned-emotion-lora
Base model
distilbert/distilbert-base-uncased