update model card README.md
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README.md
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dataset:
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name: emotion
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type: emotion
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args:
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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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- name: F1
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type: f1
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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: 0.
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- Accuracy: 0.
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- F1: 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: 64
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- eval_batch_size: 64
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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:
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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.
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| 0.
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### Framework versions
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- Transformers 4.13.0
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- Pytorch 1.
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- Datasets
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- Tokenizers 0.10.3
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dataset:
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name: emotion
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type: emotion
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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: 0.9355
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- name: F1
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type: f1
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value: 0.9356480877541032
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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: 0.1424
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- Accuracy: 0.9355
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- F1: 0.9356
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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: 5e-05
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- train_batch_size: 64
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- eval_batch_size: 64
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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: 3.0
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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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| 0.5311 | 1.0 | 250 | 0.1817 | 0.932 | 0.9317 |
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| 0.14 | 2.0 | 500 | 0.1483 | 0.9365 | 0.9368 |
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| 0.0915 | 3.0 | 750 | 0.1424 | 0.9355 | 0.9356 |
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### Framework versions
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- Transformers 4.13.0
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- Pytorch 1.10.2+cu102
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- Datasets 2.8.0
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- Tokenizers 0.10.3
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