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stackoverflow_tag_classification/initial_run/bert-base-cased/grandiose-horse-172

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README.md ADDED
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+ ---
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+ library_name: peft
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+ license: apache-2.0
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+ base_model: google-bert/bert-base-cased
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: grandiose-horse-172
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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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+ # grandiose-horse-172
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+
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+ This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6509
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+ - Hamming Loss: 0.3414
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+ - Zero One Loss: 1.0
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+ - Jaccard Score: 0.8678
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+ - Hamming Loss Optimised: 0.1121
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+ - Hamming Loss Threshold: 0.7504
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+ - Zero One Loss Optimised: 0.8812
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+ - Zero One Loss Threshold: 0.6730
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+ - Jaccard Score Optimised: 0.8449
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+ - Jaccard Score Threshold: 0.6539
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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: 1.510606094120106e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 2024
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Hamming Loss | Zero One Loss | Jaccard Score | Hamming Loss Optimised | Hamming Loss Threshold | Zero One Loss Optimised | Zero One Loss Threshold | Jaccard Score Optimised | Jaccard Score Threshold |
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+ |:-------------:|:-----:|:----:|:---------------:|:------------:|:-------------:|:-------------:|:----------------------:|:----------------------:|:-----------------------:|:-----------------------:|:-----------------------:|:-----------------------:|
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+ | No log | 1.0 | 100 | 0.7202 | 0.4325 | 1.0 | 0.8586 | 0.1123 | 0.7924 | 0.8712 | 0.7112 | 0.8203 | 0.5766 |
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+ | No log | 2.0 | 200 | 0.6922 | 0.3761 | 1.0 | 0.8520 | 0.1123 | 0.7829 | 0.8812 | 0.6982 | 0.8546 | 0.5904 |
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+ | No log | 3.0 | 300 | 0.6696 | 0.349 | 1.0 | 0.8606 | 0.1123 | 0.7641 | 0.885 | 0.6857 | 0.8436 | 0.6634 |
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+ | No log | 4.0 | 400 | 0.6555 | 0.3432 | 1.0 | 0.8662 | 0.1121 | 0.7518 | 0.8825 | 0.6757 | 0.8455 | 0.6604 |
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+ | 0.6931 | 5.0 | 500 | 0.6509 | 0.3414 | 1.0 | 0.8678 | 0.1121 | 0.7504 | 0.8812 | 0.6730 | 0.8449 | 0.6539 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.13.2
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+ - Transformers 4.47.0
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.1.0
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+ - Tokenizers 0.21.0
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