xtremedistil-emotion
This model is a fine-tuned version of microsoft/xtremedistil-l6-h256-uncased on the emotion dataset. It achieves the following results on the evaluation set:
- Accuracy: 0.9265
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 128
- eval_batch_size: 8
- seed: 42
- num_epochs: 24
Training results
Epoch Training Loss Validation Loss Accuracy 1 No log 1.238589 0.609000 2 No log 0.934423 0.714000 3 No log 0.768701 0.742000 4 1.074800 0.638208 0.805500 5 1.074800 0.551363 0.851500 6 1.074800 0.476291 0.875500 7 1.074800 0.427313 0.883500 8 0.531500 0.392633 0.886000 9 0.531500 0.357979 0.892000 10 0.531500 0.330304 0.899500 11 0.531500 0.304529 0.907000 12 0.337200 0.287447 0.918000 13 0.337200 0.277067 0.921000 14 0.337200 0.259483 0.921000 15 0.337200 0.257564 0.916500 16 0.246200 0.241970 0.919500 17 0.246200 0.241537 0.921500 18 0.246200 0.235705 0.924500 19 0.246200 0.237325 0.920500 20 0.201400 0.229699 0.923500 21 0.201400 0.227426 0.923000 22 0.201400 0.228554 0.924000 23 0.201400 0.226941 0.925500 24 0.184300 0.225816 0.926500
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Dataset used to train bergum/xtremedistil-emotion
Evaluation results
- Accuracy on emotionself-reported0.926
- Accuracy on emotiontest set verified0.926
- Precision Macro on emotiontest set verified0.886
- Precision Micro on emotiontest set verified0.926
- Precision Weighted on emotiontest set verified0.928
- Recall Macro on emotiontest set verified0.897
- Recall Micro on emotiontest set verified0.926
- Recall Weighted on emotiontest set verified0.926
- F1 Macro on emotiontest set verified0.890
- F1 Micro on emotiontest set verified0.926