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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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base_model: google/gemma-2b |
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datasets: |
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- generator |
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model-index: |
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- name: Not-so-bright-AGI-v1 |
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results: [] |
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pipeline_tag: question-answering |
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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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# Not-so-bright-AGI-v1 |
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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: 2.0548 |
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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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More information needed |
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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: 4 |
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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: 32 |
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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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| 2.9165 | 3.2 | 100 | 2.6762 | |
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| 2.419 | 6.4 | 200 | 2.3629 | |
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| 2.2343 | 9.6 | 300 | 2.2060 | |
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| 2.1459 | 12.8 | 400 | 2.1401 | |
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| 2.0944 | 16.0 | 500 | 2.1112 | |
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| 2.0679 | 19.2 | 600 | 2.0942 | |
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| 2.0496 | 22.4 | 700 | 2.0826 | |
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| 2.0375 | 25.6 | 800 | 2.0743 | |
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| 2.0213 | 28.8 | 900 | 2.0684 | |
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| 2.0148 | 32.0 | 1000 | 2.0630 | |
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| 2.0048 | 35.2 | 1100 | 2.0593 | |
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| 1.9988 | 38.4 | 1200 | 2.0575 | |
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| 1.9968 | 41.6 | 1300 | 2.0555 | |
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| 1.9908 | 44.8 | 1400 | 2.0548 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.40.0 |
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- Pytorch 2.0.1a0+cxx11.abi |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
