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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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- 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: distilbert-base-uncased-finetuned-go_emotions_20220608_1 |
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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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args: simplified |
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metrics: |
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- name: F1 |
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type: f1 |
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value: 0.5575026333429091 |
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- name: Accuracy |
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type: accuracy |
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value: 0.43641725027644673 |
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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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# distilbert-base-uncased-finetuned-go_emotions_20220608_1 |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the go_emotions dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0857 |
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- F1: 0.5575 |
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- Roc Auc: 0.7242 |
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- Accuracy: 0.4364 |
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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: 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: 5 |
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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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| 0.173 | 1.0 | 679 | 0.1074 | 0.4245 | 0.6455 | 0.2976 | |
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| 0.0989 | 2.0 | 1358 | 0.0903 | 0.5199 | 0.6974 | 0.3972 | |
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| 0.0865 | 3.0 | 2037 | 0.0868 | 0.5504 | 0.7180 | 0.4263 | |
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| 0.0806 | 4.0 | 2716 | 0.0860 | 0.5472 | 0.7160 | 0.4233 | |
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| 0.0771 | 5.0 | 3395 | 0.0857 | 0.5575 | 0.7242 | 0.4364 | |
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### Framework versions |
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- Transformers 4.19.2 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.2.2 |
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- Tokenizers 0.12.1 |
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