metadata
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: gpt-mqa-RoPE
results: []
gpt-mqa-RoPE
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 6.0885
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: 0.0003
- train_batch_size: 128
- eval_batch_size: 128
- seed: 20
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 106
- training_steps: 1060
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 9.5007 | 0.0590 | 106 | 9.2225 |
| 7.6938 | 0.1179 | 212 | 7.6025 |
| 7.0385 | 0.1769 | 318 | 6.9495 |
| 6.6472 | 0.2359 | 424 | 6.5905 |
| 6.4123 | 0.2948 | 530 | 6.3711 |
| 6.2808 | 0.3538 | 636 | 6.2347 |
| 6.1927 | 0.4127 | 742 | 6.1516 |
| 6.1486 | 0.4717 | 848 | 6.1083 |
| 6.1331 | 0.5307 | 954 | 6.0914 |
| 6.1282 | 0.5896 | 1060 | 6.0885 |
Framework versions
- Transformers 5.5.4
- Pytorch 2.11.0+cu130
- Datasets 4.8.4
- Tokenizers 0.22.2