dair-ai/emotion
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How to use gokuls/hbertv1-emotion-intermediate_KD_new with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="gokuls/hbertv1-emotion-intermediate_KD_new") # Load model directly
from transformers import AutoModelForSequenceClassification
model = AutoModelForSequenceClassification.from_pretrained("gokuls/hbertv1-emotion-intermediate_KD_new", device_map="auto")This model is a fine-tuned version of gokuls/bert_12_layer_model_v1_complete_training_new_48 on the emotion dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 3.5702 | 1.0 | 250 | 2.3579 | 0.7245 |
| 2.149 | 2.0 | 500 | 1.8353 | 0.8445 |
| 1.8068 | 3.0 | 750 | 1.6314 | 0.868 |
| 1.639 | 4.0 | 1000 | 1.5135 | 0.8875 |
| 1.5325 | 5.0 | 1250 | 1.4804 | 0.87 |
| 1.4672 | 6.0 | 1500 | 1.5219 | 0.869 |
| 1.3918 | 7.0 | 1750 | 1.4353 | 0.877 |
| 1.4349 | 8.0 | 2000 | 1.4497 | 0.8845 |
| 1.3062 | 9.0 | 2250 | 1.4030 | 0.8855 |