Qwen3-30B-A3B-Base-alpaca-th-52k-dolly-th-15k-wangchan-instruct-seed-4201
This model is a fine-tuned version of 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: 0.6674
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: 4201
- 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 |
---|---|---|---|
0.888 | 0.2299 | 10 | 1.0090 |
0.7828 | 0.4598 | 20 | 0.8235 |
0.7248 | 0.6897 | 30 | 0.7310 |
0.7106 | 0.9195 | 40 | 0.7068 |
0.6989 | 1.1379 | 50 | 0.6958 |
0.6693 | 1.3678 | 60 | 0.6871 |
0.667 | 1.5977 | 70 | 0.6809 |
0.6734 | 1.8276 | 80 | 0.6763 |
0.6343 | 2.0460 | 90 | 0.6718 |
0.6556 | 2.2759 | 100 | 0.6695 |
0.6516 | 2.5057 | 110 | 0.6680 |
0.6636 | 2.7356 | 120 | 0.6675 |
0.6357 | 2.9655 | 130 | 0.6674 |
Framework versions
- PEFT 0.15.2
- Transformers 4.52.3
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1
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Model tree for airesearch/Qwen3-30B-A3B-Base-alpaca-th-52k-dolly-th-15k-wangchan-instruct-seed-4201
Base model
Qwen/Qwen3-30B-A3B-Base