dair-ai/emotion
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How to use gokuls/hbertv2-emotion_48 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="gokuls/hbertv2-emotion_48") # Load model directly
from transformers import AutoModelForSequenceClassification
model = AutoModelForSequenceClassification.from_pretrained("gokuls/hbertv2-emotion_48", dtype="auto")This model is a fine-tuned version of gokuls/bert_12_layer_model_v2_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 |
|---|---|---|---|---|
| 1.3078 | 1.0 | 250 | 1.0127 | 0.613 |
| 0.6832 | 2.0 | 500 | 0.5913 | 0.81 |
| 0.4602 | 3.0 | 750 | 0.4422 | 0.876 |
| 0.3479 | 4.0 | 1000 | 0.5042 | 0.8575 |
| 0.2844 | 5.0 | 1250 | 0.3738 | 0.8825 |
| 0.2439 | 6.0 | 1500 | 0.3575 | 0.886 |
| 0.2029 | 7.0 | 1750 | 0.3617 | 0.8955 |
| 0.1675 | 8.0 | 2000 | 0.3826 | 0.887 |
| 0.1387 | 9.0 | 2250 | 0.3930 | 0.8875 |
| 0.1134 | 10.0 | 2500 | 0.4199 | 0.894 |