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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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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: my_awesome_model_3
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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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+ # my_awesome_model_3
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+
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+ This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0954
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+ - Accuracy: 0.9680
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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: 2
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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 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 0.09 | 200 | 0.2369 | 0.9040 |
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+ | No log | 0.19 | 400 | 0.1859 | 0.9324 |
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+ | 0.2931 | 0.28 | 600 | 0.1624 | 0.9442 |
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+ | 0.2931 | 0.38 | 800 | 0.1194 | 0.9569 |
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+ | 0.1456 | 0.47 | 1000 | 0.1245 | 0.9588 |
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+ | 0.1456 | 0.57 | 1200 | 0.1044 | 0.9617 |
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+ | 0.1456 | 0.66 | 1400 | 0.1063 | 0.9611 |
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+ | 0.1194 | 0.75 | 1600 | 0.1021 | 0.9634 |
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+ | 0.1194 | 0.85 | 1800 | 0.1618 | 0.9490 |
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+ | 0.1107 | 0.94 | 2000 | 0.1113 | 0.9643 |
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+ | 0.1107 | 1.04 | 2200 | 0.1163 | 0.9630 |
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+ | 0.1107 | 1.13 | 2400 | 0.0954 | 0.9680 |
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+ | 0.079 | 1.22 | 2600 | 0.1272 | 0.9635 |
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+ | 0.079 | 1.32 | 2800 | 0.0976 | 0.9657 |
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+ | 0.0715 | 1.41 | 3000 | 0.0995 | 0.9680 |
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+ | 0.0715 | 1.51 | 3200 | 0.0996 | 0.9660 |
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+ | 0.0715 | 1.6 | 3400 | 0.1001 | 0.9670 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.26.1
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+ - Pytorch 1.13.1+cu116
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+ - Datasets 2.10.1
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+ - Tokenizers 0.13.2