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--- |
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base_model: google/gemma-2-2b-it |
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library_name: peft |
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license: gemma |
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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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model-index: |
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- name: Gemma-2-2B_task-3_180-samples_config-2_full |
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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-2-2B_task-3_180-samples_config-2_full |
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This model is a fine-tuned version of [google/gemma-2-2b-it](https://huggingface.co./google/gemma-2-2b-it) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1691 |
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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: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 16 |
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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: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-------:|:----:|:---------------:| |
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| 1.3981 | 0.9412 | 8 | 1.3785 | |
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| 1.3072 | 2.0 | 17 | 1.2429 | |
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| 1.1985 | 2.9412 | 25 | 1.1442 | |
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| 0.9971 | 4.0 | 34 | 1.0312 | |
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| 0.9268 | 4.9412 | 42 | 0.9882 | |
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| 0.9442 | 6.0 | 51 | 0.9653 | |
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| 0.9253 | 6.9412 | 59 | 0.9537 | |
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| 0.8684 | 8.0 | 68 | 0.9479 | |
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| 0.8043 | 8.9412 | 76 | 0.9456 | |
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| 0.7924 | 10.0 | 85 | 0.9502 | |
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| 0.7535 | 10.9412 | 93 | 0.9591 | |
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| 0.694 | 12.0 | 102 | 0.9863 | |
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| 0.6881 | 12.9412 | 110 | 0.9994 | |
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| 0.6566 | 14.0 | 119 | 1.0534 | |
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| 0.5597 | 14.9412 | 127 | 1.1117 | |
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| 0.497 | 16.0 | 136 | 1.1691 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.44.0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
