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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - f1
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+ model-index:
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+ - name: distilbert-base-uncased_fold_6_binary
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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_fold_6_binary
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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 the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.6838
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+ - F1: 0.7881
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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: 16
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+ - eval_batch_size: 16
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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: 25
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | No log | 1.0 | 290 | 0.4181 | 0.7732 |
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+ | 0.4097 | 2.0 | 580 | 0.3967 | 0.7697 |
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+ | 0.4097 | 3.0 | 870 | 0.5811 | 0.7797 |
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+ | 0.2034 | 4.0 | 1160 | 0.8684 | 0.7320 |
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+ | 0.2034 | 5.0 | 1450 | 0.9116 | 0.7718 |
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+ | 0.0794 | 6.0 | 1740 | 1.0588 | 0.7690 |
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+ | 0.0278 | 7.0 | 2030 | 1.2092 | 0.7738 |
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+ | 0.0278 | 8.0 | 2320 | 1.2180 | 0.7685 |
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+ | 0.0233 | 9.0 | 2610 | 1.3005 | 0.7676 |
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+ | 0.0233 | 10.0 | 2900 | 1.4009 | 0.7634 |
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+ | 0.0093 | 11.0 | 3190 | 1.4528 | 0.7805 |
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+ | 0.0093 | 12.0 | 3480 | 1.4803 | 0.7859 |
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+ | 0.0088 | 13.0 | 3770 | 1.4775 | 0.7750 |
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+ | 0.0077 | 14.0 | 4060 | 1.6171 | 0.7699 |
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+ | 0.0077 | 15.0 | 4350 | 1.6429 | 0.7636 |
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+ | 0.0047 | 16.0 | 4640 | 1.5619 | 0.7819 |
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+ | 0.0047 | 17.0 | 4930 | 1.5833 | 0.7724 |
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+ | 0.0034 | 18.0 | 5220 | 1.6400 | 0.7853 |
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+ | 0.0008 | 19.0 | 5510 | 1.6508 | 0.7792 |
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+ | 0.0008 | 20.0 | 5800 | 1.6838 | 0.7881 |
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+ | 0.0009 | 21.0 | 6090 | 1.6339 | 0.7829 |
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+ | 0.0009 | 22.0 | 6380 | 1.6824 | 0.7806 |
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+ | 0.0016 | 23.0 | 6670 | 1.6867 | 0.7876 |
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+ | 0.0016 | 24.0 | 6960 | 1.7107 | 0.7877 |
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+ | 0.0013 | 25.0 | 7250 | 1.6933 | 0.7812 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.21.0
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+ - Pytorch 1.12.0+cu113
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+ - Datasets 2.4.0
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+ - Tokenizers 0.12.1