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update model card README.md

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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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+ model-index:
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+ - name: recipe-distilbert-s
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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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+ # recipe-distilbert-s
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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: 1.0321
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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: 256
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+ - eval_batch_size: 256
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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: 20
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+ - mixed_precision_training: Native AMP
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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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+ | 1.8594 | 1.0 | 844 | 1.4751 |
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+ | 1.4763 | 2.0 | 1688 | 1.3282 |
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+ | 1.3664 | 3.0 | 2532 | 1.2553 |
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+ | 1.2975 | 4.0 | 3376 | 1.2093 |
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+ | 1.2543 | 5.0 | 4220 | 1.1667 |
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+ | 1.2189 | 6.0 | 5064 | 1.1472 |
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+ | 1.1944 | 7.0 | 5908 | 1.1251 |
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+ | 1.1737 | 8.0 | 6752 | 1.1018 |
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+ | 1.1549 | 9.0 | 7596 | 1.0950 |
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+ | 1.1387 | 10.0 | 8440 | 1.0796 |
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+ | 1.1295 | 11.0 | 9284 | 1.0713 |
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+ | 1.1166 | 12.0 | 10128 | 1.0639 |
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+ | 1.1078 | 13.0 | 10972 | 1.0485 |
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+ | 1.099 | 14.0 | 11816 | 1.0431 |
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+ | 1.0951 | 15.0 | 12660 | 1.0425 |
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+ | 1.0874 | 16.0 | 13504 | 1.0323 |
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+ | 1.0828 | 17.0 | 14348 | 1.0368 |
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+ | 1.0802 | 18.0 | 15192 | 1.0339 |
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+ | 1.0798 | 19.0 | 16036 | 1.0247 |
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+ | 1.0758 | 20.0 | 16880 | 1.0321 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.19.0.dev0
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+ - Pytorch 1.11.0+cu102
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+ - Datasets 2.3.2
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+ - Tokenizers 0.12.1