| --- |
| library_name: transformers |
| tags: |
| - generated_from_trainer |
| datasets: |
| - arrow |
| model-index: |
| - name: moe_f2_default_trainer |
| 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. --> |
|
|
| # moe_f2_default_trainer |
| |
| This model is a fine-tuned version of [](https://huggingface.co/) on the arrow dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 5.0049 |
| |
| ## 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: 0.0001 |
| - train_batch_size: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - distributed_type: multi-GPU |
| - num_devices: 2 |
| - gradient_accumulation_steps: 16 |
| - total_train_batch_size: 1024 |
| - total_eval_batch_size: 64 |
| - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 500 |
| - training_steps: 3139 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:------:|:----:|:---------------:| |
| | No log | 0 | 0 | 10.9662 | |
| | 9.4999 | 0.9970 | 313 | 8.0448 | |
| | 5.4525 | 3.1943 | 1000 | 5.2930 | |
| | 4.3994 | 6.3886 | 2000 | 4.8620 | |
| | 3.8403 | 8.9970 | 2817 | 4.9521 | |
| | 3.6889 | 9.5829 | 3000 | 5.0029 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.51.0 |
| - Pytorch 2.7.0+cu126 |
| - Datasets 3.6.0 |
| - Tokenizers 0.21.1 |
|
|
