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update model card README.md
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README.md
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---
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license: mit
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base_model: roberta-base
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tags:
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- generated_from_trainer
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datasets:
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- imdb
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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: results
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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: imdb
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type: imdb
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config: plain_text
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split: test
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args: plain_text
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9133333333333333
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- name: F1
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type: f1
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value: 0.9161290322580645
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- name: Precision
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type: precision
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value: 0.8875
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- name: Recall
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type: recall
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value: 0.9466666666666667
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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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# results
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the imdb dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2250
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- Accuracy: 0.9133
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- F1: 0.9161
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- Precision: 0.8875
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- Recall: 0.9467
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 4
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 16
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- total_train_batch_size: 64
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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: 500
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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| 0.6922 | 0.98 | 46 | 0.6867 | 0.7433 | 0.6778 | 0.9101 | 0.54 |
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| 0.2634 | 1.98 | 93 | 0.3428 | 0.8833 | 0.8736 | 0.9528 | 0.8067 |
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| 0.1736 | 2.94 | 138 | 0.2250 | 0.9133 | 0.9161 | 0.8875 | 0.9467 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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