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lora_fine_tuned_boolq

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ library_name: peft
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+ tags:
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+ - generated_from_trainer
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+ base_model: google-bert/bert-base-uncased
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+ metrics:
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+ - accuracy
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+ - f1
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+ model-index:
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+ - name: lora_fine_tuned_boolq
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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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+ # lora_fine_tuned_boolq
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+
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+ This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5547
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+ - Accuracy: 0.7778
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+ - F1: 0.6806
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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: 2e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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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: linear
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+ - training_steps: 400
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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+ |:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
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+ | 0.6762 | 4.1667 | 50 | 0.5947 | 0.7778 | 0.6806 |
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+ | 0.6639 | 8.3333 | 100 | 0.5719 | 0.7778 | 0.6806 |
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+ | 0.6555 | 12.5 | 150 | 0.5648 | 0.7778 | 0.6806 |
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+ | 0.6605 | 16.6667 | 200 | 0.5615 | 0.7778 | 0.6806 |
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+ | 0.6612 | 20.8333 | 250 | 0.5568 | 0.7778 | 0.6806 |
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+ | 0.6508 | 25.0 | 300 | 0.5567 | 0.7778 | 0.6806 |
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+ | 0.6491 | 29.1667 | 350 | 0.5550 | 0.7778 | 0.6806 |
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+ | 0.663 | 33.3333 | 400 | 0.5547 | 0.7778 | 0.6806 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.10.1.dev0
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+ - Transformers 4.40.1
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+ - Pytorch 2.3.0
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+ - Datasets 2.19.0
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+ - Tokenizers 0.19.1
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+ "init_lora_weights": true,
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+ "loftq_config": {},
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+ "lora_alpha": 32,
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+ "peft_type": "LORA",
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