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
results: []
fine_tuned_xsum
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: 0.1573
- Accuracy: 0.9597
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 |
|---|---|---|---|---|
| 0.7991 | 0.0289 | 100 | 0.3764 | 0.8394 |
| 0.6153 | 0.0578 | 200 | 0.3492 | 0.8602 |
| 0.3929 | 0.0867 | 300 | 0.5004 | 0.8501 |
| 0.7981 | 0.1156 | 400 | 0.3459 | 0.8677 |
| 0.5853 | 0.1445 | 500 | 0.3124 | 0.8787 |
| 0.3284 | 0.1734 | 600 | 0.2438 | 0.9308 |
| 0.3591 | 0.2023 | 700 | 0.2842 | 0.9041 |
| 0.332 | 0.2311 | 800 | 0.3904 | 0.9038 |
| 0.3424 | 0.2600 | 900 | 0.2234 | 0.9402 |
| 0.2609 | 0.2889 | 1000 | 0.2586 | 0.9249 |
| 0.3036 | 0.3178 | 1100 | 0.2775 | 0.9204 |
| 0.2429 | 0.3467 | 1200 | 0.1521 | 0.9441 |
| 0.2495 | 0.3756 | 1300 | 0.2326 | 0.9512 |
| 0.2486 | 0.4045 | 1400 | 0.2712 | 0.9467 |
| 0.1711 | 0.4334 | 1500 | 0.1573 | 0.9597 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu126
- Datasets 3.3.2
- Tokenizers 0.21.0