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Saving best model of baseline_BERT_50K_steps to hub

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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: bert-base-uncased
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - arxiv_dataset
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+ metrics:
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+ - accuracy
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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: baseline_BERT_50K_steps
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+ results:
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+ - task:
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+ name: Text Classification
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+ type: text-classification
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+ dataset:
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+ name: arxiv_dataset
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+ type: arxiv_dataset
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+ config: default
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+ split: train
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9936787420400056
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+ - name: Precision
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+ type: precision
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+ value: 0.7967781908302355
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+ - name: Recall
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+ type: recall
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+ value: 0.4734468476760239
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+ - name: F1
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+ type: f1
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+ value: 0.5939610876970152
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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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+ # baseline_BERT_50K_steps
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+
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+ This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the arxiv_dataset dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0192
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+ - Accuracy: 0.9937
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+ - Precision: 0.7968
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+ - Recall: 0.4734
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+ - F1: 0.5940
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+ - Hamming: 0.0063
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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: 2e-05
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+ - train_batch_size: 6
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+ - eval_batch_size: 6
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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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+ - lr_scheduler_warmup_ratio: 0.1
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+ - training_steps: 50000
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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 | Precision | Recall | F1 | Hamming |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
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+ | 0.0343 | 0.03 | 10000 | 0.0315 | 0.9912 | 0.7679 | 0.1370 | 0.2326 | 0.0088 |
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+ | 0.0244 | 0.06 | 20000 | 0.0234 | 0.9925 | 0.7813 | 0.3262 | 0.4602 | 0.0075 |
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+ | 0.0219 | 0.09 | 30000 | 0.0210 | 0.9931 | 0.7572 | 0.4320 | 0.5502 | 0.0069 |
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+ | 0.0204 | 0.12 | 40000 | 0.0197 | 0.9935 | 0.7738 | 0.4711 | 0.5857 | 0.0065 |
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+ | 0.0197 | 0.15 | 50000 | 0.0192 | 0.9937 | 0.7968 | 0.4734 | 0.5940 | 0.0063 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.37.2
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+ - Pytorch 1.12.1+cu113
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.1
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+ {
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+ "epoch": 0.15,
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+ "train_runtime": 18671.9874,
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+ "train_samples_per_second": 16.067,
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+ "train_steps_per_second": 2.678
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+ }
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