metadata
library_name: peft
license: other
base_model: Qwen/Qwen2.5-7B-Instruct
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: Limo_qwen
results: []
Limo_qwen
This model is a fine-tuned version of Qwen/Qwen2.5-7B-Instruct on the Limo dataset. It achieves the following results on the evaluation set:
- Loss: 0.7120
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: 8e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- total_eval_batch_size: 4
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.8842 | 1.0 | 12 | 0.8997 |
| 0.8086 | 2.0 | 24 | 0.8223 |
| 0.7502 | 3.0 | 36 | 0.7781 |
| 0.7287 | 4.0 | 48 | 0.7514 |
| 0.6899 | 5.0 | 60 | 0.7341 |
| 0.6934 | 6.0 | 72 | 0.7228 |
| 0.6727 | 7.0 | 84 | 0.7168 |
| 0.69 | 8.0 | 96 | 0.7134 |
| 0.6892 | 9.0 | 108 | 0.7124 |
| 0.6735 | 10.0 | 120 | 0.7120 |
Framework versions
- PEFT 0.15.2
- Transformers 4.52.4
- Pytorch 2.8.0+cu129
- Datasets 3.6.0
- Tokenizers 0.21.4