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---
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen3-0.6B
tags:
- generated_from_trainer
model-index:
- name: sft-count_loss-Qwen3-0.6B-mle0.5-ul0.5-tox0-e4
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. -->
# sft-count_loss-Qwen3-0.6B-mle0.5-ul0.5-tox0-e4
This model is a fine-tuned version of [Qwen/Qwen3-0.6B](https://huggingface.co/Qwen/Qwen3-0.6B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9505
## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_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_steps: 5
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.7934 | 0.2899 | 200 | 1.3768 |
| 2.6787 | 0.5797 | 400 | 1.3584 |
| 2.7074 | 0.8696 | 600 | 1.3443 |
| 1.8508 | 1.1594 | 800 | 1.3934 |
| 1.9016 | 1.4493 | 1000 | 1.4017 |
| 1.8603 | 1.7391 | 1200 | 1.4073 |
| 1.7469 | 2.0290 | 1400 | 1.6987 |
| 0.9924 | 2.3188 | 1600 | 1.7187 |
| 1.0118 | 2.6087 | 1800 | 1.7246 |
| 0.9845 | 2.8986 | 2000 | 1.7222 |
| 0.5651 | 3.1884 | 2200 | 1.9391 |
| 0.5605 | 3.4783 | 2400 | 1.9573 |
| 0.553 | 3.7681 | 2600 | 1.9505 |
### Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1