metadata
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen2-1.5B
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fine_tuned_hswag_callback10
results: []
fine_tuned_hswag_callback10
This model is a fine-tuned version of Qwen/Qwen2-1.5B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1861
- Accuracy: 0.9602
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7551 | 0.0322 | 100 | 0.4489 | 0.9012 |
| 0.3977 | 0.0644 | 200 | 0.5959 | 0.8943 |
| 0.3608 | 0.0966 | 300 | 0.2267 | 0.9258 |
| 0.3092 | 0.1287 | 400 | 0.1801 | 0.9374 |
| 0.1932 | 0.1609 | 500 | 0.1921 | 0.9562 |
| 0.1405 | 0.1931 | 600 | 0.2487 | 0.9573 |
| 0.3093 | 0.2253 | 700 | 0.1245 | 0.9573 |
| 0.1804 | 0.2575 | 800 | 0.1496 | 0.9602 |
| 0.1717 | 0.2897 | 900 | 0.1923 | 0.9573 |
| 0.1986 | 0.3219 | 1000 | 0.4235 | 0.9167 |
| 0.1786 | 0.3540 | 1100 | 0.1436 | 0.9591 |
| 0.1563 | 0.3862 | 1200 | 0.2635 | 0.9468 |
| 0.188 | 0.4184 | 1300 | 0.1891 | 0.9540 |
| 0.137 | 0.4506 | 1400 | 0.2017 | 0.9348 |
| 0.1438 | 0.4828 | 1500 | 0.1510 | 0.9660 |
| 0.1241 | 0.5150 | 1600 | 0.2152 | 0.9551 |
| 0.1793 | 0.5472 | 1700 | 0.1861 | 0.9602 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu126
- Datasets 3.3.2
- Tokenizers 0.21.0