roberta-base
This model is a fine-tuned model that was trained using Amazon SageMaker and the new Hugging Face Deep Learning container.
- Problem type: Multi Class Text Classification (emotion detection).
It achieves the following results on the evaluation set:
- Loss: 0.1613253802061081
- f1: 0.9413321705151999
Hyperparameters
{
"epochs": 10,
"train_batch_size": 16,
"learning_rate": 3e-5,
"weight_decay":0.01,
"load_best_model_at_end": true,
"model_name":"roberta-base",
"do_eval": True,
"load_best_model_at_end":True
}
Validation Metrics
key | value |
---|---|
eval_accuracy | 0.941 |
eval_f1 | 0.9413321705151999 |
eval_loss | 0.1613253802061081 |
eval_recall | 0.941 |
eval_precision | 0.9419519436781406 |
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the model is not deployed on the HF Inference API.
Dataset used to train Jorgeutd/sagemaker-roberta-base-emotion
Evaluation results
- Validation Accuracy on emotionself-reported94.100
- Validation F1 on emotionself-reported94.130
- Accuracy on emotiontest set verified0.931
- Precision Macro on emotiontest set verified0.883
- Precision Micro on emotiontest set verified0.931
- Precision Weighted on emotiontest set verified0.934
- Recall Macro on emotiontest set verified0.909
- Recall Micro on emotiontest set verified0.931
- Recall Weighted on emotiontest set verified0.931
- F1 Macro on emotiontest set verified0.895