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Advince/distilbert-base-uncased-lora-toxic-classification

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README.md ADDED
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+ ---
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+ base_model: distilbert-base-uncased
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+ library_name: peft
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+ license: apache-2.0
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+ metrics:
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+ - accuracy
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+ tags:
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+ - generated_from_trainer
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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: 1.3115
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+ - Accuracy: {'accuracy': 0.8125}
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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: 15
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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 | 431 | 0.6279 | {'accuracy': 0.7135416666666666} |
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+ | 0.7248 | 2.0 | 862 | 0.5949 | {'accuracy': 0.7604166666666666} |
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+ | 0.5433 | 3.0 | 1293 | 0.5986 | {'accuracy': 0.8072916666666666} |
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+ | 0.4762 | 4.0 | 1724 | 0.6967 | {'accuracy': 0.8125} |
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+ | 0.3971 | 5.0 | 2155 | 0.7136 | {'accuracy': 0.8229166666666666} |
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+ | 0.3471 | 6.0 | 2586 | 0.8597 | {'accuracy': 0.8177083333333334} |
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+ | 0.2695 | 7.0 | 3017 | 1.0061 | {'accuracy': 0.8072916666666666} |
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+ | 0.2695 | 8.0 | 3448 | 0.7674 | {'accuracy': 0.8333333333333334} |
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+ | 0.2417 | 9.0 | 3879 | 1.2479 | {'accuracy': 0.828125} |
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+ | 0.2079 | 10.0 | 4310 | 1.0548 | {'accuracy': 0.8177083333333334} |
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+ | 0.1941 | 11.0 | 4741 | 1.0516 | {'accuracy': 0.8229166666666666} |
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+ | 0.1711 | 12.0 | 5172 | 1.2246 | {'accuracy': 0.828125} |
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+ | 0.1253 | 13.0 | 5603 | 1.2416 | {'accuracy': 0.8177083333333334} |
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+ | 0.0918 | 14.0 | 6034 | 1.3199 | {'accuracy': 0.8229166666666666} |
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+ | 0.0918 | 15.0 | 6465 | 1.3115 | {'accuracy': 0.8125} |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.13.0
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+ - Transformers 4.44.2
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+ - Pytorch 2.4.1+cu121
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+ - Datasets 3.0.0
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+ - Tokenizers 0.19.1
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+ "use_rslora": false
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