GemmaSheep-2B-LORA-TUNED
This model is a fine-tuned version of google/gemma-2b on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 2.1445
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
databricks/databricks-dolly-15k
Training Hardware
This model was trained using Intel(R) Data Center GPU Max 1100
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 593
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.8445 | 0.82 | 100 | 2.5144 |
2.4282 | 1.64 | 200 | 2.2987 |
2.2735 | 2.46 | 300 | 2.2079 |
2.2193 | 3.28 | 400 | 2.1661 |
2.19 | 4.1 | 500 | 2.1445 |
Framework versions
- PEFT 0.10.0
- Transformers 4.39.3
- Pytorch 2.0.1a0+cxx11.abi
- Datasets 2.18.0
- Tokenizers 0.15.2
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google/gemma-2b
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