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: 1.1367
- Accuracy: {'accuracy': 0.881}
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: 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 250 | 0.5355 | {'accuracy': 0.834} |
| 0.4237 | 2.0 | 500 | 0.5577 | {'accuracy': 0.867} |
| 0.4237 | 3.0 | 750 | 0.7444 | {'accuracy': 0.868} |
| 0.1861 | 4.0 | 1000 | 0.6896 | {'accuracy': 0.884} |
| 0.1861 | 5.0 | 1250 | 0.9201 | {'accuracy': 0.881} |
| 0.0388 | 6.0 | 1500 | 0.9153 | {'accuracy': 0.894} |
| 0.0388 | 7.0 | 1750 | 1.1074 | {'accuracy': 0.877} |
| 0.0076 | 8.0 | 2000 | 1.0988 | {'accuracy': 0.883} |
| 0.0076 | 9.0 | 2250 | 1.1251 | {'accuracy': 0.878} |
| 0.0029 | 10.0 | 2500 | 1.1367 | {'accuracy': 0.881} |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for GauravGyansri/distilbert-base-uncased-lora-text-classification
Base model
distilbert/distilbert-base-uncased