outputs/gemma-3-270m-codealpaca-finetune
This model is a fine-tuned version of google/gemma-3-270m-it on the HuggingFaceH4/CodeAlpaca_20K dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Memory/max Memory Active(gib): 8.51
- Memory/max Memory Allocated(gib): 8.51
- Memory/device Memory Reserved(gib): 10.27
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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 34
- training_steps: 348
Training results
| Training Loss | Epoch | Step | Validation Loss | Memory Active(gib) | Memory Allocated(gib) | Memory Reserved(gib) |
|---|---|---|---|---|---|---|
| No log | 0 | 0 | nan | 5.84 | 5.84 | 5.86 |
| 0.0 | 0.9978 | 116 | nan | 8.51 | 8.51 | 10.27 |
| 0.0 | 1.9892 | 232 | nan | 8.51 | 8.51 | 10.27 |
| 0.0 | 2.9806 | 348 | nan | 8.51 | 8.51 | 10.27 |
Framework versions
- Transformers 4.55.0
- Pytorch 2.6.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4
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Safetensors
Model size
0.3B params
Tensor type
BF16
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