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ApplicantTrackingSystemBERT

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bert
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+ ---
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: training_bert
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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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+ # training_bert
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+
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+ This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 4.0495
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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: 5e-05
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+ - train_batch_size: 128
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+ - eval_batch_size: 128
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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: 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 |
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+ |:-------------:|:-----:|:-----:|:---------------:|
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+ | 6.7862 | 0.11 | 500 | 6.9461 |
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+ | 5.9428 | 0.22 | 1000 | 6.4640 |
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+ | 5.5463 | 0.33 | 1500 | 6.2736 |
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+ | 5.1871 | 0.44 | 2000 | 5.8517 |
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+ | 4.896 | 0.55 | 2500 | 5.6070 |
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+ | 4.6557 | 0.66 | 3000 | 5.4669 |
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+ | 4.4832 | 0.77 | 3500 | 5.3318 |
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+ | 4.3368 | 0.88 | 4000 | 5.2414 |
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+ | 4.1887 | 0.99 | 4500 | 5.0666 |
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+ | 4.053 | 1.1 | 5000 | 4.9532 |
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+ | 3.9653 | 1.21 | 5500 | 4.8288 |
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+ | 3.8865 | 1.33 | 6000 | 4.6741 |
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+ | 3.8294 | 1.44 | 6500 | 4.7943 |
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+ | 3.7565 | 1.55 | 7000 | 4.7336 |
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+ | 3.673 | 1.66 | 7500 | 4.4760 |
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+ | 3.6447 | 1.77 | 8000 | 4.5856 |
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+ | 3.5808 | 1.88 | 8500 | 4.6133 |
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+ | 3.5329 | 1.99 | 9000 | 4.4766 |
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+ | 3.4916 | 2.1 | 9500 | 4.5085 |
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+ | 3.4392 | 2.21 | 10000 | 4.5306 |
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+ | 3.4333 | 2.32 | 10500 | 4.5433 |
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+ | 3.3905 | 2.43 | 11000 | 4.1829 |
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+ | 3.3701 | 2.54 | 11500 | 4.2976 |
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+ | 3.3345 | 2.65 | 12000 | 4.2817 |
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+ | 3.2815 | 2.76 | 12500 | 4.3146 |
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+ | 3.2689 | 2.87 | 13000 | 4.2634 |
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+ | 3.2401 | 2.98 | 13500 | 4.0907 |
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+ | 3.2068 | 3.09 | 14000 | 4.1130 |
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+ | 3.2097 | 3.2 | 14500 | 4.2001 |
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+ | 3.1627 | 3.31 | 15000 | 4.0852 |
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+ | 3.1647 | 3.42 | 15500 | 4.0383 |
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+ | 3.1294 | 3.53 | 16000 | 3.9377 |
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+ | 3.1166 | 3.64 | 16500 | 4.0733 |
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+ | 3.1028 | 3.75 | 17000 | 3.8429 |
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+ | 3.0903 | 3.86 | 17500 | 4.1127 |
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+ | 3.0877 | 3.98 | 18000 | 3.8605 |
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+ | 3.0407 | 4.09 | 18500 | 3.8482 |
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+ | 3.0452 | 4.2 | 19000 | 4.0345 |
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+ | 3.0496 | 4.31 | 19500 | 3.8602 |
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+ | 3.0229 | 4.42 | 20000 | 4.2268 |
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+ | 3.0157 | 4.53 | 20500 | 3.8028 |
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+ | 3.0037 | 4.64 | 21000 | 3.8668 |
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+ | 2.9992 | 4.75 | 21500 | 3.9542 |
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+ | 3.016 | 4.86 | 22000 | 3.9090 |
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+ | 2.9804 | 4.97 | 22500 | 4.0495 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.25.1
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+ - Pytorch 1.8.0+cu111
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+ - Datasets 2.7.1
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+ - Tokenizers 0.13.2