---
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen3-1.7B
tags:
- generated_from_trainer
model-index:
- name: unsup-Qwen3-1.7B-datav3
  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. -->

# unsup-Qwen3-1.7B-datav3

This model is a fine-tuned version of [Qwen/Qwen3-1.7B](https://huggingface.co/Qwen/Qwen3-1.7B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2568

## 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: 0.0003
- train_batch_size: 128
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-07 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 4.2641        | 0.0624 | 1000  | 0.3924          |
| 4.2102        | 0.1247 | 2000  | 0.3755          |
| 3.6754        | 0.1871 | 3000  | 0.3278          |
| 3.4875        | 0.2494 | 4000  | 0.3120          |
| 3.4383        | 0.3118 | 5000  | 0.2955          |
| 3.0117        | 0.3741 | 6000  | 0.2865          |
| 2.9805        | 0.4365 | 7000  | 0.2790          |
| 2.5125        | 0.4988 | 8000  | 0.2720          |
| 2.4559        | 0.5612 | 9000  | 0.2633          |
| 2.5172        | 0.6235 | 10000 | 0.2570          |
| 2.2059        | 0.6859 | 11000 | 0.2528          |
| 1.973         | 0.7482 | 12000 | 0.2564          |
| 1.9219        | 0.8106 | 13000 | 0.2556          |
| 1.643         | 0.8729 | 14000 | 0.2570          |
| 1.9918        | 0.9353 | 15000 | 0.2564          |
| 1.8969        | 0.9976 | 16000 | 0.2568          |


### Framework versions

- Transformers 4.51.0
- Pytorch 2.8.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.0