metadata
library_name: transformers
tags:
- generated_from_trainer
datasets:
- arrow
model-index:
- name: moe_f1_ctrl
results: []
moe_f1_ctrl
This model is a fine-tuned version of on the arrow dataset. It achieves the following results on the evaluation set:
- Loss: 4.6829
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: 2987
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0 | 0 | 10.9698 |
| 5.8228 | 2.9973 | 894 | 5.2290 |
| 5.0921 | 3.3547 | 1000 | 5.0673 |
| 4.4924 | 5.9973 | 1788 | 4.5960 |
| 4.1215 | 6.7095 | 2000 | 4.5916 |
| 3.6247 | 10.0234 | 2987 | 4.6829 |
| 3.6247 | 10.0268 | 2988 | 4.6829 |
Framework versions
- Transformers 4.51.0
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1