76 lines
2.1 KiB
Markdown
76 lines
2.1 KiB
Markdown
---
|
|
library_name: transformers
|
|
license: other
|
|
base_model: Qwen/Qwen3-4B-Instruct-2507
|
|
tags:
|
|
- llama-factory
|
|
- full
|
|
- generated_from_trainer
|
|
model-index:
|
|
- name: sft_cot
|
|
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_cot
|
|
|
|
This model is a fine-tuned version of [Qwen/Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507) on the scope_sft_cot dataset.
|
|
It achieves the following results on the evaluation set:
|
|
- Loss: 0.3770
|
|
|
|
## 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: 1e-05
|
|
- train_batch_size: 1
|
|
- eval_batch_size: 2
|
|
- seed: 42
|
|
- gradient_accumulation_steps: 8
|
|
- 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_ratio: 0.1
|
|
- num_epochs: 1.0
|
|
|
|
### Training results
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss |
|
|
|:-------------:|:------:|:----:|:---------------:|
|
|
| 0.5282 | 0.0763 | 500 | 0.5320 |
|
|
| 0.5294 | 0.1526 | 1000 | 0.5253 |
|
|
| 0.5116 | 0.2289 | 1500 | 0.5039 |
|
|
| 0.5121 | 0.3052 | 2000 | 0.4850 |
|
|
| 0.4778 | 0.3815 | 2500 | 0.4666 |
|
|
| 0.4823 | 0.4578 | 3000 | 0.4533 |
|
|
| 0.4292 | 0.5341 | 3500 | 0.4343 |
|
|
| 0.4333 | 0.6104 | 4000 | 0.4167 |
|
|
| 0.4153 | 0.6867 | 4500 | 0.4017 |
|
|
| 0.3973 | 0.7630 | 5000 | 0.3908 |
|
|
| 0.4168 | 0.8393 | 5500 | 0.3823 |
|
|
| 0.3918 | 0.9156 | 6000 | 0.3777 |
|
|
| 0.3942 | 0.9919 | 6500 | 0.3770 |
|
|
|
|
|
|
### Framework versions
|
|
|
|
- Transformers 4.57.1
|
|
- Pytorch 2.7.1+cu126
|
|
- Datasets 3.6.0
|
|
- Tokenizers 0.22.1
|