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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-3_180-samples_config-2_full
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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-3_180-samples_config-2_full
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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: 1.1691
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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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+ | 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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+
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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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