---
library_name: peft
license: other
base_model: Qwen/Qwen2.5-72B
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: qwen2.5-72b-openreviewer-mvp-1-full-review-r128
  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. -->

# qwen2.5-72b-openreviewer-mvp-1-full-review-r128

This model is a fine-tuned version of [Qwen/Qwen2.5-72B](https://huggingface.co/Qwen/Qwen2.5-72B) on the openreview_full_review dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3836

## 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: 2
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 8
- 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: 5.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.532         | 0.5091 | 600  | 1.5193          |
| 1.4402        | 1.0182 | 1200 | 1.4956          |
| 1.434         | 1.5274 | 1800 | 1.4622          |
| 1.2638        | 2.0365 | 2400 | 1.4360          |
| 1.2456        | 2.5456 | 3000 | 1.4051          |
| 1.104         | 3.0547 | 3600 | 1.3918          |
| 1.0918        | 3.5639 | 4200 | 1.3742          |
| 1.0143        | 4.0730 | 4800 | 1.3840          |
| 1.0092        | 4.5821 | 5400 | 1.3840          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.46.1
- Pytorch 2.5.1
- Datasets 3.1.0
- Tokenizers 0.20.3