metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-lora-text-classification
results: []
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: 0.8839
- Accuracy: {'accuracy': 0.901}
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 | 0.3334 | {'accuracy': 0.892} |
| 0.3999 | 2.0 | 500 | 0.3850 | {'accuracy': 0.892} |
| 0.3999 | 3.0 | 750 | 0.4382 | {'accuracy': 0.895} |
| 0.2004 | 4.0 | 1000 | 0.5518 | {'accuracy': 0.895} |
| 0.2004 | 5.0 | 1250 | 0.6261 | {'accuracy': 0.899} |
| 0.0674 | 6.0 | 1500 | 0.8357 | {'accuracy': 0.892} |
| 0.0674 | 7.0 | 1750 | 0.8303 | {'accuracy': 0.901} |
| 0.0301 | 8.0 | 2000 | 0.8756 | {'accuracy': 0.894} |
| 0.0301 | 9.0 | 2250 | 0.8779 | {'accuracy': 0.897} |
| 0.0028 | 10.0 | 2500 | 0.8839 | {'accuracy': 0.901} |
Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1
- Datasets 2.14.4
- Tokenizers 0.15.0