AndersGiovanni commited on
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End of training

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README.md ADDED
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+ ---
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+ license: other
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+ base_model: google/gemma-2b
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: gemma-2b
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+ results: []
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+ library_name: peft
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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-2b
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+
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+ This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.2320
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+ - Accuracy: 0.1180
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+ - Precision: 0.5651
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+ - Recall: 0.3145
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+ - F1: 0.4041
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+ - Hamming Loss: 0.1988
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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: 2
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+ - eval_batch_size: 2
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: constant
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+ - lr_scheduler_warmup_ratio: 0.05
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+ - num_epochs: 10
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.5.0
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+ - Transformers 4.38.2
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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+ "peft_type": "LORA",
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+ "r": 2,
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+ "target_modules": [
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+ "q_proj",
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+ "gate_proj",
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+ "up_proj",
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+ "down_proj"
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+ ],
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+ "task_type": "SEQ_CLS"
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+ }
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