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--- |
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license: gemma |
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base_model: google/gemma-2-9b-it |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: gemma-2-9b-it-lora-commonsense |
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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/yspkm/PrunePath-LoRA/runs/8piyty9j) |
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# gemma-2-9b-it-lora-commonsense |
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This model is a fine-tuned version of [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8229 |
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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: 0.0001 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 128 |
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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_steps: 100 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.0188 | 0.1503 | 200 | 0.9641 | |
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| 0.9971 | 0.3007 | 400 | 0.9404 | |
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| 0.9827 | 0.4510 | 600 | 0.9288 | |
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| 0.9748 | 0.6013 | 800 | 0.9194 | |
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| 0.971 | 0.7516 | 1000 | 0.9055 | |
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| 0.957 | 0.9020 | 1200 | 0.8970 | |
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| 0.9005 | 1.0523 | 1400 | 0.8874 | |
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| 0.8876 | 1.2026 | 1600 | 0.8748 | |
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| 0.8782 | 1.3529 | 1800 | 0.8640 | |
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| 0.8896 | 1.5033 | 2000 | 0.8489 | |
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| 0.8814 | 1.6536 | 2200 | 0.8417 | |
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| 0.8666 | 1.8039 | 2400 | 0.8325 | |
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| 0.8674 | 1.9542 | 2600 | 0.8307 | |
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| 0.8116 | 2.1046 | 2800 | 0.8366 | |
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| 0.8032 | 2.2549 | 3000 | 0.8291 | |
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| 0.8103 | 2.4052 | 3200 | 0.8265 | |
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| 0.8165 | 2.5556 | 3400 | 0.8245 | |
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| 0.8085 | 2.7059 | 3600 | 0.8242 | |
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| 0.8121 | 2.8562 | 3800 | 0.8229 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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