metadata
library_name: transformers
tags:
- generated_from_trainer
datasets:
- arrow
model-index:
- name: moe_f2_ctrl
results: []
moe_f2_ctrl
This model is a fine-tuned version of on the arrow dataset. It achieves the following results on the evaluation set:
- Loss: 5.0297
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 | 10.9924 |
| 5.9544 | 2.9970 | 939 | 5.3775 |
| 5.2693 | 3.1943 | 1000 | 5.3046 |
| 4.5724 | 5.9970 | 1878 | 4.8553 |
| 4.3168 | 6.3886 | 2000 | 4.8878 |
| 3.7561 | 9.5829 | 3000 | 5.0274 |
| 3.7561 | 10.0287 | 3139 | 5.0297 |
| 3.7561 | 10.0319 | 3140 | 5.0297 |
Framework versions
- Transformers 4.51.0
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1