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library_name: peft
license: other
base_model: Qwen/Qwen2.5-7B-Instruct
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: Bespoke_17k_lora
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Bespoke_17k_lora
This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the Bespoke_17k dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5167
## 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: 5e-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: 0.1
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8425 | 0.1290 | 32 | 0.7648 |
| 0.7261 | 0.2580 | 64 | 0.6592 |
| 0.6559 | 0.3870 | 96 | 0.5983 |
| 0.6316 | 0.5160 | 128 | 0.5707 |
| 0.6236 | 0.6450 | 160 | 0.5557 |
| 0.6061 | 0.7740 | 192 | 0.5463 |
| 0.593 | 0.9030 | 224 | 0.5396 |
| 0.5771 | 1.0282 | 256 | 0.5375 |
| 0.5953 | 1.1572 | 288 | 0.5316 |
| 0.5735 | 1.2862 | 320 | 0.5289 |
| 0.5752 | 1.4152 | 352 | 0.5264 |
| 0.5903 | 1.5442 | 384 | 0.5242 |
| 0.5662 | 1.6732 | 416 | 0.5225 |
| 0.5656 | 1.8022 | 448 | 0.5209 |
| 0.574 | 1.9312 | 480 | 0.5199 |
| 0.5692 | 2.0564 | 512 | 0.5193 |
| 0.5656 | 2.1854 | 544 | 0.5183 |
| 0.5654 | 2.3144 | 576 | 0.5177 |
| 0.5664 | 2.4434 | 608 | 0.5173 |
| 0.5714 | 2.5724 | 640 | 0.5170 |
| 0.5656 | 2.7014 | 672 | 0.5168 |
| 0.5681 | 2.8304 | 704 | 0.5168 |
| 0.5541 | 2.9594 | 736 | 0.5167 |
### Framework versions
- PEFT 0.15.2
- Transformers 4.52.4
- Pytorch 2.8.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.4 |