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: 1.0878
- Accuracy: {'accuracy': 0.88}
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 | 0.3774 | {'accuracy': 0.863} |
| 0.3793 | 2.0 | 500 | 0.3980 | {'accuracy': 0.884} |
| 0.3793 | 3.0 | 750 | 0.6004 | {'accuracy': 0.885} |
| 0.1356 | 4.0 | 1000 | 0.7604 | {'accuracy': 0.884} |
| 0.1356 | 5.0 | 1250 | 0.8298 | {'accuracy': 0.887} |
| 0.0431 | 6.0 | 1500 | 0.9589 | {'accuracy': 0.883} |
| 0.0431 | 7.0 | 1750 | 1.0109 | {'accuracy': 0.883} |
| 0.0202 | 8.0 | 2000 | 1.0334 | {'accuracy': 0.884} |
| 0.0202 | 9.0 | 2250 | 1.0635 | {'accuracy': 0.88} |
| 0.0095 | 10.0 | 2500 | 1.0878 | {'accuracy': 0.88} |
Framework versions
- PEFT 0.13.0
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1