metadata
base_model: distilbert-base-uncased
library_name: peft
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
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 the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6464
- Accuracy: {'accuracy': 0.84}
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 | 0.5728 | {'accuracy': 0.824} |
| 0.4384 | 2.0 | 500 | 0.6861 | {'accuracy': 0.84} |
| 0.4384 | 3.0 | 750 | 1.1608 | {'accuracy': 0.812} |
| 0.1949 | 4.0 | 1000 | 1.0198 | {'accuracy': 0.826} |
| 0.1949 | 5.0 | 1250 | 1.1314 | {'accuracy': 0.838} |
| 0.0612 | 6.0 | 1500 | 1.3810 | {'accuracy': 0.844} |
| 0.0612 | 7.0 | 1750 | 1.6426 | {'accuracy': 0.832} |
| 0.0164 | 8.0 | 2000 | 1.6141 | {'accuracy': 0.844} |
| 0.0164 | 9.0 | 2250 | 1.6768 | {'accuracy': 0.842} |
| 0.0075 | 10.0 | 2500 | 1.6464 | {'accuracy': 0.84} |
Framework versions
- PEFT 0.12.0
- Transformers 4.42.4
- Pytorch 2.3.1
- Datasets 2.20.0
- Tokenizers 0.19.1