Gemma-2B-finetuning-italian-version
This model is a fine-tuned version of google/gemma-2-2B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4752
- Model Preparation Time: 0.0044
- Accuracy: 0.8190
- F1 Macro: 0.8230
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Accuracy | F1 Macro |
---|---|---|---|---|---|---|
1.0205 | 1.0 | 368 | 0.9795 | 0.0044 | 0.6163 | 0.6032 |
0.5492 | 2.0 | 736 | 0.5696 | 0.0044 | 0.7565 | 0.7630 |
0.4625 | 3.0 | 1104 | 0.5029 | 0.0044 | 0.7966 | 0.8017 |
0.3503 | 4.0 | 1472 | 0.4814 | 0.0044 | 0.8054 | 0.8133 |
0.3745 | 5.0 | 1840 | 0.4974 | 0.0044 | 0.7986 | 0.8057 |
0.3279 | 6.0 | 2208 | 0.4988 | 0.0044 | 0.8068 | 0.8141 |
Framework versions
- PEFT 0.14.0
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.0
- Tokenizers 0.21.0
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