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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-2_60-samples_config-2_auto |
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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-2_60-samples_config-2_auto |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8866 |
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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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| 0.9552 | 0.6957 | 2 | 1.0746 | |
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| 0.9555 | 1.7391 | 5 | 1.0326 | |
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| 0.8712 | 2.7826 | 8 | 0.9149 | |
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| 0.7712 | 3.8261 | 11 | 0.8319 | |
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| 0.6958 | 4.8696 | 14 | 0.7876 | |
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| 0.6428 | 5.9130 | 17 | 0.7529 | |
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| 0.5843 | 6.9565 | 20 | 0.7262 | |
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| 0.561 | 8.0 | 23 | 0.7111 | |
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| 0.5211 | 8.6957 | 25 | 0.7022 | |
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| 0.456 | 9.7391 | 28 | 0.6938 | |
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| 0.4502 | 10.7826 | 31 | 0.6950 | |
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| 0.3993 | 11.8261 | 34 | 0.7011 | |
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| 0.3589 | 12.8696 | 37 | 0.7186 | |
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| 0.3157 | 13.9130 | 40 | 0.7445 | |
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| 0.2717 | 14.9565 | 43 | 0.7838 | |
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| 0.2344 | 16.0 | 46 | 0.8412 | |
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| 0.1863 | 16.6957 | 48 | 0.8866 | |
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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 |
