---
library_name: peft
license: other
base_model: Qwen/Qwen3-30B-A3B-Base
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: Qwen3-30B-A3B-Base-alpaca-th-52k-dolly-th-15k-wangchan-instruct-seed-2405
  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. -->

# Qwen3-30B-A3B-Base-alpaca-th-52k-dolly-th-15k-wangchan-instruct-seed-2405

This model is a fine-tuned version of [Qwen/Qwen3-30B-A3B-Base](https://huggingface.co//Qwen/Qwen3-30B-A3B-Base) on the alpaca-th-52k, the dolly-th-15k and the wangchan-instruct datasets.
It achieves the following results on the evaluation set:
- Loss: 0.6619

## 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: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 2405
- distributed_type: multi-GPU
- num_devices: 128
- gradient_accumulation_steps: 8
- total_train_batch_size: 2048
- total_eval_batch_size: 256
- optimizer: Use OptimizerNames.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: 3.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8866        | 0.2299 | 10   | 1.0011          |
| 0.7869        | 0.4598 | 20   | 0.8175          |
| 0.724         | 0.6897 | 30   | 0.7251          |
| 0.702         | 0.9195 | 40   | 0.7024          |
| 0.6926        | 1.1379 | 50   | 0.6904          |
| 0.6795        | 1.3678 | 60   | 0.6821          |
| 0.6694        | 1.5977 | 70   | 0.6757          |
| 0.674         | 1.8276 | 80   | 0.6708          |
| 0.6543        | 2.0460 | 90   | 0.6660          |
| 0.6492        | 2.2759 | 100  | 0.6639          |
| 0.6508        | 2.5057 | 110  | 0.6626          |
| 0.656         | 2.7356 | 120  | 0.6621          |
| 0.6492        | 2.9655 | 130  | 0.6619          |


### Framework versions

- PEFT 0.15.2
- Transformers 4.52.3
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1