metadata
library_name: transformers
license: other
base_model: Qwen/Qwen1.5-MoE-A2.7B
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fine_tuned_per_domain_balanced_moe_lr
results: []
fine_tuned_per_domain_balanced_moe_lr
This model is a fine-tuned version of Qwen/Qwen1.5-MoE-A2.7B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6637
- Accuracy: 0.8800
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: 5e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- 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: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.2077 | 0.0029 | 500 | 1.9021 | 0.8317 |
| 0.9585 | 0.0057 | 1000 | 2.2812 | 0.8299 |
| 1.479 | 0.0086 | 1500 | 1.5268 | 0.8066 |
| 1.1161 | 0.0114 | 2000 | 0.9974 | 0.8550 |
| 0.8147 | 0.0143 | 2500 | 0.6406 | 0.8926 |
| 1.4377 | 0.0172 | 3000 | 1.5956 | 0.8156 |
| 0.6541 | 0.0200 | 3500 | 0.9456 | 0.8720 |
| 0.9445 | 0.0229 | 4000 | 0.6637 | 0.8800 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu126
- Datasets 3.3.2
- Tokenizers 0.21.0