Gemma2 LoRA Adapters
Collection
Gemma2 LoRA adapters fine-tuned using SFT in TRL on diverse tasks such as coding, SQL, Japanese to English, and function calling
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6 items
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Updated
gemma-2-2B-it-function_calling
This model is a fine-tuned version of google/gemma-2-2b-it on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 0.8928
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.8466 | 0.9994 | 398 | 0.8928 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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