1.9 KiB
1.9 KiB
library_name, tags, model-index
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| transformers |
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slm-125m-tutor
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0573
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 32
- 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: 0.03
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.3378 | 0.2863 | 500 | 1.2903 |
| 1.2281 | 0.5726 | 1000 | 1.1914 |
| 1.1361 | 0.8589 | 1500 | 1.1385 |
| 0.9816 | 1.1449 | 2000 | 1.1079 |
| 0.9342 | 1.4311 | 2500 | 1.0880 |
| 0.9271 | 1.7174 | 3000 | 1.0697 |
| 0.9189 | 2.0034 | 3500 | 1.0578 |
| 0.7955 | 2.2897 | 4000 | 1.0619 |
| 0.8140 | 2.5760 | 4500 | 1.0589 |
| 0.8316 | 2.8623 | 5000 | 1.0573 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2