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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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+ - f1
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+ - precision
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+ - recall
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+ model-index:
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+ - name: sentiment_test2
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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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+ # sentiment_test2
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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 an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4885
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+ - Y True: [0 0 0 0 0 0 2 0 0 0 0 0 0 2 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0
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+ 0 0 0 0 0 0 0 0 0 0 0 0 2 2 2 2 1 2 2 1 1 2 2 2 0 2 2 1 1 2 2 2 1 0 2 2 2
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+ 2 2 2 2 1 2 2 2 2 1 2 2 2 2 2 2 1 2 2 2 2 0 2 2 2 2 2 2 1 2 2 2 2 2 1 1 1
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+ 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
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+ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1]
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+ - Y Pred: [0 0 0 0 0 0 2 0 0 0 2 0 0 2 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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+ 0 0 0 0 0 0 0 0 0 0 0 0 2 2 2 2 1 2 2 2 2 2 2 2 0 2 2 2 2 2 2 2 2 2 2 2 2
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+ 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1
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+ 1 1 1 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 2 1 1 1
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+ 1 1 1 1 2 1 1 1 0 1 1 1 1 1 2 1 1 1 1]
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+ - Accuracy: 0.8743
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+ - F1: 0.8753
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+ - Precision: 0.8944
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+ - Recall: 0.8743
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+ - Confusion Matrix: [[46 1 2]
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+ [ 1 52 15]
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+ [ 1 1 48]]
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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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+ - lr_scheduler_warmup_steps: 50
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+ - num_epochs: 5
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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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+
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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 1.12.1+cu113
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+ - Datasets 2.9.0
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+ - Tokenizers 0.13.2