distilbert-base-uncased-lora-text-classification
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: 0.4402
- Accuracy: {'accuracy': 0.874}
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: 2
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 250 | 0.4001 | {'accuracy': 0.866} |
0.336 | 2.0 | 500 | 0.4402 | {'accuracy': 0.874} |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.2+cpu
- Datasets 2.19.2
- Tokenizers 0.13.3
Model tree for rinki24/distilbert-base-uncased-lora-text-classification
Base model
distilbert/distilbert-base-uncased