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--- |
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language: en |
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widget: |
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- text: "I am really upset that I have to call up to three times to the number on the back of my insurance card for my call to be answer" |
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tags: |
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- sagemaker |
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- roberta-base |
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- text classification |
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license: apache-2.0 |
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datasets: |
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- emotion |
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model-index: |
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- name: sagemaker-roberta-base-emotion |
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results: |
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- task: |
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name: Multi Class Text Classification |
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type: text-classification |
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dataset: |
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name: "emotion" |
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type: emotion |
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metrics: |
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- name: Validation Accuracy |
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type: accuracy |
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value: 94.1 |
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- name: Validation F1 |
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type: f1 |
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value: 94.13 |
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--- |
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## roberta-base |
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This model is a fine-tuned model that was trained using Amazon SageMaker and the new Hugging Face Deep Learning container. |
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- Problem type: Multi Class Text Classification (emotion detection). |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1613253802061081 |
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- f1: 0.9413321705151999 |
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## Hyperparameters |
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```json |
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{ |
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"epochs": 10, |
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"train_batch_size": 16, |
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"learning_rate": 3e-5, |
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"weight_decay":0.01, |
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"load_best_model_at_end": true, |
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"model_name":"roberta-base", |
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"do_eval": True, |
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"load_best_model_at_end":True |
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} |
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``` |
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## Validation Metrics |
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| key | value | |
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| --- | ----- | |
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| eval_accuracy | 0.941 | |
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| eval_f1 | 0.9413321705151999 | |
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| eval_loss | 0.1613253802061081| |
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| eval_recall | 0.941 | |
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| eval_precision | 0.9419519436781406 | |
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