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update model card README.md
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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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- emotion
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metrics:
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- accuracy
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model-index:
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- name: distiled_flip_model_emotion_alpha_0.8_epoch7_v1
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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: emotion
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type: emotion
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config: default
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split: train
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args: default
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9435
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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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# distiled_flip_model_emotion_alpha_0.8_epoch7_v1
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This model is a fine-tuned version of [ArafatBHossain/distill_bert_fine_tuned_emotion_dataset](https://huggingface.co/ArafatBHossain/distill_bert_fine_tuned_emotion_dataset) on the emotion dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1583
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- Accuracy: 0.9435
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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: 8
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- eval_batch_size: 8
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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: 7
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|
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| 0.2013 | 1.0 | 2000 | 0.2653 | 0.9355 |
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| 0.1625 | 2.0 | 4000 | 0.2537 | 0.9365 |
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| 0.1262 | 3.0 | 6000 | 0.1934 | 0.935 |
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| 0.1048 | 4.0 | 8000 | 0.1813 | 0.9435 |
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| 0.0777 | 5.0 | 10000 | 0.1500 | 0.941 |
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| 0.0614 | 6.0 | 12000 | 0.1591 | 0.944 |
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| 0.0465 | 7.0 | 14000 | 0.1583 | 0.9435 |
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### Framework versions
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- Transformers 4.23.1
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- Pytorch 1.11.0
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- Datasets 2.6.1
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- Tokenizers 0.12.1
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