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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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datasets: |
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- go_emotions |
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metrics: |
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- f1 |
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- accuracy |
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model-index: |
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- name: pretrained_model |
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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: go_emotions |
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type: go_emotions |
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config: simplified |
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split: validation |
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args: simplified |
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metrics: |
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- name: F1 |
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type: f1 |
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value: 0.586801681970308 |
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- name: Accuracy |
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type: accuracy |
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value: 0.4821231109472908 |
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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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# pretrained_model |
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This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the go_emotions dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0568 |
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- F1: 0.5868 |
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- Roc Auc: 0.7616 |
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- Accuracy: 0.4821 |
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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: 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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| |
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| 0.1205 | 1.0 | 679 | 0.0865 | 0.5632 | 0.7347 | 0.4458 | |
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| 0.0859 | 2.0 | 1358 | 0.0829 | 0.5717 | 0.7378 | 0.4521 | |
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| 0.0727 | 3.0 | 2037 | 0.0827 | 0.5897 | 0.7523 | 0.4753 | |
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| 0.0629 | 4.0 | 2716 | 0.0857 | 0.5808 | 0.7535 | 0.4652 | |
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| 0.0568 | 5.0 | 3395 | 0.0904 | 0.5868 | 0.7616 | 0.4821 | |
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| 0.0423 | 6.0 | 4074 | 0.0989 | 0.5806 | 0.7682 | 0.4724 | |
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| 0.0344 | 7.0 | 4753 | 0.1079 | 0.5736 | 0.7657 | 0.4650 | |
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| 0.0296 | 8.0 | 5432 | 0.1158 | 0.5637 | 0.7649 | 0.4504 | |
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| 0.0206 | 9.0 | 6111 | 0.1200 | 0.5674 | 0.7689 | 0.4486 | |
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| 0.0177 | 10.0 | 6790 | 0.1240 | 0.5728 | 0.7737 | 0.4547 | |
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### Framework versions |
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- Transformers 4.26.0 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.9.0 |
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- Tokenizers 0.13.2 |
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