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--- |
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license: gemma |
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library_name: peft |
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tags: |
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- trl |
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- sft |
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- generated_from_trainer |
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- ipex |
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- GPU Max 1100 |
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- intel |
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datasets: |
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- generator |
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- databricks/databricks-dolly-15k |
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base_model: google/gemma-2b |
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model-index: |
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- name: gemma-2b-dolly-qa |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# gemma-2b-dolly-qa |
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This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the generator dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0215 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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databricks/databricks-dolly-15k |
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## Training Hardware |
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This model was trained using Intel(R) Data Center GPU Max 1100 |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.05 |
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- training_steps: 1480 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 2.9198 | 1.64 | 100 | 2.5675 | |
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| 2.437 | 3.28 | 200 | 2.2818 | |
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| 2.2514 | 4.92 | 300 | 2.1677 | |
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| 2.1587 | 6.56 | 400 | 2.1038 | |
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| 2.116 | 8.2 | 500 | 2.0741 | |
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| 2.0794 | 9.84 | 600 | 2.0576 | |
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| 2.0663 | 11.48 | 700 | 2.0467 | |
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| 2.0494 | 13.11 | 800 | 2.0394 | |
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| 2.0449 | 14.75 | 900 | 2.0336 | |
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| 2.0336 | 16.39 | 1000 | 2.0293 | |
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| 2.0281 | 18.03 | 1100 | 2.0262 | |
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| 2.0172 | 19.67 | 1200 | 2.0240 | |
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| 2.0227 | 21.31 | 1300 | 2.0227 | |
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| 2.0128 | 22.95 | 1400 | 2.0215 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.39.3 |
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- Pytorch 2.0.1a0+cxx11.abi |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
