---
library_name: peft
license: apache-2.0
base_model: Qwen/Qwen2.5-7B-Instruct
tags:
- llama-factory
- generated_from_trainer
model-index:
- name: Qwen2.5-7B-Instruct-PsyCourse-doc-fold8
  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. -->

# Qwen2.5-7B-Instruct-PsyCourse-doc-fold8

This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0711

## 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.1678        | 0.3951 | 10   | 0.1853          |
| 0.2057        | 0.7901 | 20   | 0.1200          |
| 0.0673        | 1.1852 | 30   | 0.0915          |
| 0.0982        | 1.5802 | 40   | 0.0821          |
| 0.0891        | 1.9753 | 50   | 0.0771          |
| 0.0763        | 2.3704 | 60   | 0.0749          |
| 0.0509        | 2.7654 | 70   | 0.0729          |
| 0.0463        | 3.1605 | 80   | 0.0721          |
| 0.0305        | 3.5556 | 90   | 0.0715          |
| 0.0505        | 3.9506 | 100  | 0.0713          |
| 0.0645        | 4.3457 | 110  | 0.0711          |
| 0.0858        | 4.7407 | 120  | 0.0711          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3