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_xsum_balanced
results: []
fine_tuned_xsum_balanced
This model is a fine-tuned version of Qwen/Qwen2-1.5B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1586
- Accuracy: 0.9660
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: 32
- eval_batch_size: 32
- 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 |
|---|---|---|---|---|
| 0.5027 | 0.3774 | 100 | 0.2355 | 0.9002 |
| 0.2228 | 0.7547 | 200 | 0.1387 | 0.9544 |
| 0.1361 | 1.1321 | 300 | 0.3597 | 0.9183 |
| 0.0728 | 1.5094 | 400 | 0.2921 | 0.9395 |
| 0.0538 | 1.8868 | 500 | 0.1586 | 0.9660 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu126
- Datasets 3.3.2
- Tokenizers 0.21.0