update model card README.md
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README.md
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name: emotion
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type: emotion
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config: split
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split: validation
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args: split
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.
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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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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
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It achieves the following results on the evaluation set:
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- Loss:
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- Accuracy: 0.
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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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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### Training results
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| Training Loss | Epoch | Step
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### Framework versions
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- Transformers 4.26.1
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- Pytorch
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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name: emotion
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type: emotion
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config: split
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split: validation
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args: split
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.939
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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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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2100
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- Accuracy: 0.939
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-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: 16000
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- num_epochs: 10
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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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| 1.6731 | 1.0 | 1000 | 1.5737 | 0.4805 |
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| 1.224 | 2.0 | 2000 | 1.1049 | 0.5915 |
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| 0.8266 | 3.0 | 3000 | 0.7033 | 0.761 |
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| 0.4635 | 4.0 | 4000 | 0.3884 | 0.8845 |
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| 0.2832 | 5.0 | 5000 | 0.2466 | 0.9145 |
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| 0.1855 | 6.0 | 6000 | 0.2112 | 0.926 |
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| 0.1552 | 7.0 | 7000 | 0.1978 | 0.9285 |
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| 0.1426 | 8.0 | 8000 | 0.1937 | 0.9345 |
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| 0.1308 | 9.0 | 9000 | 0.2093 | 0.932 |
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| 0.1127 | 10.0 | 10000 | 0.2100 | 0.939 |
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### Framework versions
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- Transformers 4.26.1
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- Pytorch 1.13.1+cu117
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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