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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-7b |
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datasets: |
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- generator |
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model-index: |
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- name: gemma7b-summarize-gpt4o-80k |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/chansung18/huggingface/runs/oor99p6r) |
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# gemma7b-summarize-gpt4o-80k |
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This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the generator dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.9801 |
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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 procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 4 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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- total_eval_batch_size: 4 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.9152 | 0.9982 | 275 | 2.1950 | |
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| 0.8104 | 2.0 | 551 | 2.1405 | |
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| 0.7914 | 2.9982 | 826 | 2.1592 | |
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| 0.6978 | 4.0 | 1102 | 2.2176 | |
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| 0.6386 | 4.9982 | 1377 | 2.3272 | |
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| 0.5725 | 6.0 | 1653 | 2.4713 | |
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| 0.5089 | 6.9982 | 1928 | 2.6491 | |
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| 0.4678 | 8.0 | 2204 | 2.8434 | |
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| 0.433 | 8.9982 | 2479 | 2.9604 | |
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| 0.4229 | 9.9819 | 2750 | 2.9801 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.41.0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
