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update model card README.md

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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: BT5153-kaggle-sentiment-model-3000-samples
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  results: []
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  # BT5153-kaggle-sentiment-model-3000-samples
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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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  ## Model description
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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: 5
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  ### Training results
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  ### Framework versions
 
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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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  model-index:
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  - name: BT5153-kaggle-sentiment-model-3000-samples
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  results: []
 
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  # BT5153-kaggle-sentiment-model-3000-samples
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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: 0.6160
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+ - Accuracy: 0.9270
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+ - F1: 0.9288
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  ## Model description
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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: 32
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+ - eval_batch_size: 32
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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: 15
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 0.2851 | 1.0 | 625 | 0.2058 | 0.9216 | 0.9231 |
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+ | 0.1735 | 2.0 | 1250 | 0.2257 | 0.9244 | 0.9258 |
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+ | 0.121 | 3.0 | 1875 | 0.2907 | 0.9232 | 0.9251 |
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+ | 0.0525 | 4.0 | 2500 | 0.3607 | 0.9194 | 0.9219 |
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+ | 0.0381 | 5.0 | 3125 | 0.4109 | 0.9216 | 0.9233 |
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+ | 0.0257 | 6.0 | 3750 | 0.4142 | 0.9232 | 0.9244 |
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+ | 0.0192 | 7.0 | 4375 | 0.4321 | 0.9230 | 0.9233 |
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+ | 0.0126 | 8.0 | 5000 | 0.4745 | 0.9250 | 0.9278 |
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+ | 0.01 | 9.0 | 5625 | 0.5053 | 0.9240 | 0.9246 |
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+ | 0.0091 | 10.0 | 6250 | 0.5256 | 0.9240 | 0.9267 |
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+ | 0.0062 | 11.0 | 6875 | 0.5798 | 0.9246 | 0.9255 |
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+ | 0.0033 | 12.0 | 7500 | 0.5935 | 0.9242 | 0.9262 |
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+ | 0.0019 | 13.0 | 8125 | 0.5891 | 0.9286 | 0.9303 |
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+ | 0.0018 | 14.0 | 8750 | 0.6176 | 0.9266 | 0.9287 |
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+ | 0.0001 | 15.0 | 9375 | 0.6160 | 0.9270 | 0.9288 |
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  ### Framework versions