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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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model-index:
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- name: bert_emo_classifier
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results: []
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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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# bert_emo_classifier
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the emotion dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2652
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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: 2e-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: 4
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 0.8874 | 0.25 | 500 | 0.4256 |
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| 0.3255 | 0.5 | 1000 | 0.3233 |
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| 0.2754 | 0.75 | 1500 | 0.2736 |
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| 0.242 | 1.0 | 2000 | 0.2263 |
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| 0.1661 | 1.25 | 2500 | 0.2118 |
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| 0.1614 | 1.5 | 3000 | 0.1812 |
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| 0.1434 | 1.75 | 3500 | 0.1924 |
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| 0.1629 | 2.0 | 4000 | 0.1766 |
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| 0.1066 | 2.25 | 4500 | 0.2100 |
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| 0.1313 | 2.5 | 5000 | 0.1996 |
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| 0.1113 | 2.75 | 5500 | 0.2185 |
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| 0.115 | 3.0 | 6000 | 0.2406 |
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| 0.0697 | 3.25 | 6500 | 0.2485 |
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| 0.0835 | 3.5 | 7000 | 0.2391 |
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| 0.0637 | 3.75 | 7500 | 0.2695 |
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| 0.0707 | 4.0 | 8000 | 0.2652 |
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### Framework versions
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- Transformers 4.15.0
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- Pytorch 1.12.1+cu113
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- Datasets 2.4.0
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- Tokenizers 0.10.3
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