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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: 0.3768 |
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## Target Labels |
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label: a classification label, with possible values including |
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- sadness : 0 |
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- joy : 1 |
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- love : 2 |
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- anger : 3 |
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- fear : 4 |
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- surprise : 5 |
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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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| 0.1497 | 0.25 | 500 | 0.2911 | |
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| 0.1221 | 0.5 | 1000 | 0.3190 | |
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| 0.108 | 0.75 | 1500 | 0.3343 | |
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| 0.1296 | 1.0 | 2000 | 0.2803 | |
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| 0.0611 | 1.25 | 2500 | 0.3392 | |
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| 0.0651 | 1.5 | 3000 | 0.3400 | |
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| 0.0588 | 1.75 | 3500 | 0.3733 | |
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| 0.0993 | 2.0 | 4000 | 0.3672 | |
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| 0.0385 | 2.25 | 4500 | 0.4041 | |
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| 0.0509 | 2.5 | 5000 | 0.3906 | |
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| 0.0651 | 2.75 | 5500 | 0.3809 | |
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| 0.0693 | 3.0 | 6000 | 0.3944 | |
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| 0.0471 | 3.25 | 6500 | 0.3926 | |
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| 0.0462 | 3.5 | 7000 | 0.3837 | |
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| 0.0326 | 3.75 | 7500 | 0.3752 | |
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| 0.0233 | 4.0 | 8000 | 0.3768 | |
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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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