| | --- |
| | library_name: peft |
| | license: other |
| | base_model: Qwen/Qwen3-Coder-30B-A3B-Instruct |
| | tags: |
| | - base_model:adapter:Qwen/Qwen3-Coder-30B-A3B-Instruct |
| | - llama-factory |
| | - lora |
| | - transformers |
| | metrics: |
| | - accuracy |
| | pipeline_tag: text-generation |
| | model-index: |
| | - name: factory_qwen_results1 |
| | 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. --> |
| |
|
| | # factory_qwen_results1 |
| |
|
| | This model is a fine-tuned version of [Qwen/Qwen3-Coder-30B-A3B-Instruct](https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct) on the train dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.1022 |
| | - Accuracy: 0.9780 |
| |
|
| | ## 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: 0.0005 |
| | - train_batch_size: 1 |
| | - eval_batch_size: 2 |
| | - seed: 42 |
| | - distributed_type: multi-GPU |
| | - num_devices: 4 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 8 |
| | - total_eval_batch_size: 8 |
| | - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 50 |
| | - num_epochs: 3.0 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | | 0.3137 | 0.0724 | 30 | 0.3017 | 0.9260 | |
| | | 0.2642 | 0.1448 | 60 | 0.2687 | 0.9343 | |
| | | 0.2464 | 0.2171 | 90 | 0.2397 | 0.9387 | |
| | | 0.2345 | 0.2895 | 120 | 0.2179 | 0.9462 | |
| | | 0.2104 | 0.3619 | 150 | 0.2028 | 0.9488 | |
| | | 0.1645 | 0.4343 | 180 | 0.2001 | 0.9499 | |
| | | 0.1761 | 0.5066 | 210 | 0.1826 | 0.9543 | |
| | | 0.1668 | 0.5790 | 240 | 0.1741 | 0.9568 | |
| | | 0.156 | 0.6514 | 270 | 0.1672 | 0.9566 | |
| | | 0.1416 | 0.7238 | 300 | 0.1686 | 0.9553 | |
| | | 0.1361 | 0.7961 | 330 | 0.1587 | 0.9592 | |
| | | 0.162 | 0.8685 | 360 | 0.1539 | 0.9607 | |
| | | 0.1177 | 0.9409 | 390 | 0.1495 | 0.9621 | |
| | | 0.1276 | 1.0121 | 420 | 0.1450 | 0.9640 | |
| | | 0.113 | 1.0844 | 450 | 0.1454 | 0.9626 | |
| | | 0.0844 | 1.1568 | 480 | 0.1387 | 0.9642 | |
| | | 0.1035 | 1.2292 | 510 | 0.1353 | 0.9660 | |
| | | 0.0903 | 1.3016 | 540 | 0.1352 | 0.9660 | |
| | | 0.0927 | 1.3739 | 570 | 0.1316 | 0.9672 | |
| | | 0.1017 | 1.4463 | 600 | 0.1259 | 0.9695 | |
| | | 0.0805 | 1.5187 | 630 | 0.1295 | 0.9691 | |
| | | 0.1307 | 1.5911 | 660 | 0.1211 | 0.9709 | |
| | | 0.0863 | 1.6634 | 690 | 0.1184 | 0.9711 | |
| | | 0.065 | 1.7358 | 720 | 0.1169 | 0.9714 | |
| | | 0.0899 | 1.8082 | 750 | 0.1112 | 0.9724 | |
| | | 0.0736 | 1.8806 | 780 | 0.1083 | 0.9734 | |
| | | 0.0772 | 1.9530 | 810 | 0.1094 | 0.9728 | |
| | | 0.047 | 2.0241 | 840 | 0.1118 | 0.9734 | |
| | | 0.0389 | 2.0965 | 870 | 0.1143 | 0.9735 | |
| | | 0.0519 | 2.1689 | 900 | 0.1111 | 0.9742 | |
| | | 0.0417 | 2.2413 | 930 | 0.1100 | 0.9751 | |
| | | 0.0485 | 2.3136 | 960 | 0.1085 | 0.9748 | |
| | | 0.0539 | 2.3860 | 990 | 0.1055 | 0.9758 | |
| | | 0.031 | 2.4584 | 1020 | 0.1068 | 0.9760 | |
| | | 0.0367 | 2.5308 | 1050 | 0.1076 | 0.9761 | |
| | | 0.0294 | 2.6031 | 1080 | 0.1054 | 0.9773 | |
| | | 0.0329 | 2.6755 | 1110 | 0.1049 | 0.9771 | |
| | | 0.0358 | 2.7479 | 1140 | 0.1027 | 0.9773 | |
| | | 0.0321 | 2.8203 | 1170 | 0.1033 | 0.9776 | |
| | | 0.0337 | 2.8926 | 1200 | 0.1033 | 0.9777 | |
| | | 0.0456 | 2.9650 | 1230 | 0.1022 | 0.9780 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - PEFT 0.17.1 |
| | - Transformers 4.57.1 |
| | - Pytorch 2.10.0+cu128 |
| | - Datasets 4.0.0 |
| | - Tokenizers 0.22.2 |
