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End of training

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README.md ADDED
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+ ---
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+ license: mit
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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: roberta-large
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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: roberta-large-peft-p-tuning
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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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+ # roberta-large-peft-p-tuning
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+
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+ This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6299
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+ - Accuracy: 0.6649
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+ - F1: 0.7987
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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: 0.001
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+ - train_batch_size: 96
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+ - eval_batch_size: 96
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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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+ - num_epochs: 2
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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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+ | No log | 1.0 | 39 | 0.6309 | 0.6649 | 0.7987 |
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+ | No log | 2.0 | 78 | 0.6299 | 0.6649 | 0.7987 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.10.0
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+ - Transformers 4.40.1
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.0
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+ - Tokenizers 0.19.1
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+ "encoder_reparameterization_type": "MLP",
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+ "num_virtual_tokens": 20,
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+ "peft_type": "P_TUNING",
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