distilbert-base-uncased-lora-text-classification
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: 0.7678
- Accuracy: {'accuracy': 0.895}
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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 125 | 0.2777 | {'accuracy': 0.88} |
| No log | 2.0 | 250 | 0.4062 | {'accuracy': 0.872} |
| No log | 3.0 | 375 | 0.4406 | {'accuracy': 0.891} |
| 0.2605 | 4.0 | 500 | 0.4675 | {'accuracy': 0.898} |
| 0.2605 | 5.0 | 625 | 0.6199 | {'accuracy': 0.89} |
| 0.2605 | 6.0 | 750 | 0.6202 | {'accuracy': 0.897} |
| 0.2605 | 7.0 | 875 | 0.7120 | {'accuracy': 0.888} |
| 0.0386 | 8.0 | 1000 | 0.7659 | {'accuracy': 0.89} |
| 0.0386 | 9.0 | 1125 | 0.7548 | {'accuracy': 0.895} |
| 0.0386 | 10.0 | 1250 | 0.7678 | {'accuracy': 0.895} |
Framework versions
- PEFT 0.11.1
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for SathwikBalu/distilbert-base-uncased-lora-text-classification
Base model
distilbert/distilbert-base-uncased