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shawhin/distilbert-base-uncased-lora-text-classification

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: distilbert-base-uncased
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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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+ model-index:
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+ - name: distilbert-base-uncased-lora-text-classification
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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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+ # distilbert-base-uncased-lora-text-classification
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+
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+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8720
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+ - Accuracy: {'accuracy': 0.894}
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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: 4
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+ - eval_batch_size: 4
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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: 10
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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 |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------------------:|
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+ | No log | 1.0 | 250 | 0.2692 | {'accuracy': 0.901} |
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+ | 0.4047 | 2.0 | 500 | 0.5088 | {'accuracy': 0.883} |
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+ | 0.4047 | 3.0 | 750 | 0.6266 | {'accuracy': 0.886} |
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+ | 0.2421 | 4.0 | 1000 | 0.6066 | {'accuracy': 0.895} |
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+ | 0.2421 | 5.0 | 1250 | 0.6501 | {'accuracy': 0.88} |
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+ | 0.0951 | 6.0 | 1500 | 0.7872 | {'accuracy': 0.877} |
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+ | 0.0951 | 7.0 | 1750 | 0.8000 | {'accuracy': 0.891} |
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+ | 0.0231 | 8.0 | 2000 | 0.9661 | {'accuracy': 0.88} |
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+ | 0.0231 | 9.0 | 2250 | 0.8709 | {'accuracy': 0.894} |
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+ | 0.0166 | 10.0 | 2500 | 0.8720 | {'accuracy': 0.894} |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.1
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.7
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+ - Tokenizers 0.14.1
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+ "lora_alpha": 32,
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+ "lora_dropout": 0.01,
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+ "peft_type": "LORA",
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