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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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+ datasets:
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+ - tweet_eval
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+ metrics:
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+ - f1
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+ model-index:
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+ - name: sentiment_trained_1234567
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+ results:
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+ - task:
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+ name: Text Classification
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+ type: text-classification
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+ dataset:
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+ name: tweet_eval
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+ type: tweet_eval
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+ args: sentiment
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+ metrics:
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+ - name: F1
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+ type: f1
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+ value: 0.7165064254565859
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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_trained_1234567
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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 tweet_eval dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.2854
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+ - F1: 0.7165
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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: 1.2140338797769864e-05
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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+ - seed: 1234567
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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: 4
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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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+ | 0.6603 | 1.0 | 11404 | 0.7020 | 0.6992 |
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+ | 0.5978 | 2.0 | 22808 | 0.8024 | 0.7151 |
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+ | 0.5495 | 3.0 | 34212 | 1.0837 | 0.7139 |
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+ | 0.4026 | 4.0 | 45616 | 1.2854 | 0.7165 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.12.5
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+ - Pytorch 1.9.1
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+ - Datasets 1.16.1
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+ - Tokenizers 0.10.3