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metadata
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: []

Bespoke_17k_lora

This model is a fine-tuned version of 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