---
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