distilbert-base-uncased-lora-financial-sentiment-analysis
This model is a fine-tuned version of distilbert-base-uncased on the financial_phrasebank dataset. It achieves the following results on the evaluation set:
- Loss: 0.0787
- Accuracy: {'accuracy': 0.9823788546255506}
Model description
More information needed
Intended uses & limitations
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Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 4
- eval_batch_size: 4
- 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 |
|---|---|---|---|---|
| 0.1615 | 1.0 | 510 | 0.0830 | {'accuracy': 0.973568281938326} |
| 0.1076 | 2.0 | 1020 | 0.0787 | {'accuracy': 0.9823788546255506} |
| 0.0558 | 3.0 | 1530 | 0.1102 | {'accuracy': 0.9647577092511013} |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for hdupouy/distilbert-base-uncased-lora-financial-sentiment-analysis
Base model
distilbert/distilbert-base-uncased