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stackoverflow_tag_classification/initial_run/bert-base-cased/aged-colt-222

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README.md ADDED
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+ ---
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+ library_name: transformers
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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: aged-colt-222
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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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+ # aged-colt-222
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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: 0.2040
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+ - Hamming Loss: 0.0629
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+ - Zero One Loss: 0.3725
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+ - Jaccard Score: 0.3164
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+ - Hamming Loss Optimised: 0.0602
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+ - Hamming Loss Threshold: 0.6941
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+ - Zero One Loss Optimised: 0.3712
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+ - Zero One Loss Threshold: 0.5690
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+ - Jaccard Score Optimised: 0.3027
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+ - Jaccard Score Threshold: 0.3189
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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: 1.8777284034581645e-05
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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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: 8
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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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+ | 0.2942 | 1.0 | 800 | 0.1817 | 0.0614 | 0.515 | 0.4782 | 0.0599 | 0.4035 | 0.4463 | 0.3226 | 0.3475 | 0.2729 |
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+ | 0.1593 | 2.0 | 1600 | 0.1695 | 0.0586 | 0.4062 | 0.3618 | 0.0585 | 0.4832 | 0.395 | 0.4651 | 0.3226 | 0.2867 |
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+ | 0.1236 | 3.0 | 2400 | 0.1682 | 0.0594 | 0.3888 | 0.3403 | 0.0564 | 0.6322 | 0.375 | 0.4467 | 0.3003 | 0.2734 |
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+ | 0.1007 | 4.0 | 3200 | 0.1784 | 0.0574 | 0.3625 | 0.3143 | 0.0571 | 0.5063 | 0.3612 | 0.4823 | 0.3035 | 0.2923 |
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+ | 0.0775 | 5.0 | 4000 | 0.1822 | 0.0615 | 0.3662 | 0.3159 | 0.0581 | 0.7021 | 0.3675 | 0.4750 | 0.3041 | 0.3292 |
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+ | 0.059 | 6.0 | 4800 | 0.1951 | 0.0633 | 0.3688 | 0.3113 | 0.06 | 0.7800 | 0.3675 | 0.5584 | 0.2981 | 0.3377 |
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+ | 0.0474 | 7.0 | 5600 | 0.2031 | 0.0636 | 0.38 | 0.3242 | 0.06 | 0.7791 | 0.375 | 0.5376 | 0.3068 | 0.1991 |
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+ | 0.0406 | 8.0 | 6400 | 0.2040 | 0.0629 | 0.3725 | 0.3164 | 0.0602 | 0.6941 | 0.3712 | 0.5690 | 0.3027 | 0.3189 |
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+
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+
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+ ### Framework versions
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+
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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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