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README.md ADDED
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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-1_120-samples_config-2_full_auto
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+ results: []
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+ ---
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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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+
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+ # Gemma-2-2B_task-1_120-samples_config-2_full_auto
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+
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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: 1.5847
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-------:|:----:|:---------------:|
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+ | 2.2743 | 0.9091 | 5 | 2.2774 |
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+ | 2.2016 | 2.0 | 11 | 1.9581 |
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+ | 1.6799 | 2.9091 | 16 | 1.5711 |
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+ | 1.3079 | 4.0 | 22 | 1.2308 |
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+ | 1.0919 | 4.9091 | 27 | 1.0583 |
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+ | 0.9651 | 6.0 | 33 | 0.9889 |
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+ | 0.8719 | 6.9091 | 38 | 0.9588 |
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+ | 0.8299 | 8.0 | 44 | 0.9332 |
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+ | 0.7912 | 8.9091 | 49 | 0.9282 |
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+ | 0.692 | 10.0 | 55 | 0.9332 |
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+ | 0.63 | 10.9091 | 60 | 0.9539 |
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+ | 0.5784 | 12.0 | 66 | 1.0078 |
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+ | 0.4937 | 12.9091 | 71 | 1.0819 |
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+ | 0.4029 | 14.0 | 77 | 1.2032 |
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+ | 0.3117 | 14.9091 | 82 | 1.3912 |
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+ | 0.2521 | 16.0 | 88 | 1.5847 |
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+
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+
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+ ### Framework versions
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+
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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
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