dair-ai/emotion
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How to use gokuls/hbertv2-emotion_48_KD with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="gokuls/hbertv2-emotion_48_KD") # Load model directly
from transformers import AutoModelForSequenceClassification
model = AutoModelForSequenceClassification.from_pretrained("gokuls/hbertv2-emotion_48_KD", dtype="auto")This model is a fine-tuned version of gokuls/bert_12_layer_model_v2_complete_training_new_48_KD 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 |
|---|---|---|---|---|
| 1.5998 | 1.0 | 250 | 1.5899 | 0.352 |
| 1.5872 | 2.0 | 500 | 1.5967 | 0.275 |
| 1.6045 | 3.0 | 750 | 1.6220 | 0.275 |
| 1.5911 | 4.0 | 1000 | 1.4863 | 0.502 |
| 1.3919 | 5.0 | 1250 | 1.3375 | 0.5325 |
| 1.2936 | 6.0 | 1500 | 1.3029 | 0.546 |
| 1.2151 | 7.0 | 1750 | 1.2297 | 0.559 |
| 1.1985 | 8.0 | 2000 | 1.2658 | 0.551 |
| 1.1637 | 9.0 | 2250 | 1.1574 | 0.577 |
| 1.0928 | 10.0 | 2500 | 1.1141 | 0.581 |