dair-ai/emotion
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How to use gokuls/add-bert-emotion_24 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="gokuls/add-bert-emotion_24") # Load model directly
from transformers import AutoModelForSequenceClassification
model = AutoModelForSequenceClassification.from_pretrained("gokuls/add-bert-emotion_24", dtype="auto")This model is a fine-tuned version of gokuls/add_bert_12_layer_model_complete_training_new 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 |
|---|---|---|---|---|
| 1.6013 | 1.0 | 250 | 1.5840 | 0.3435 |
| 1.5884 | 2.0 | 500 | 1.5993 | 0.275 |
| 1.5783 | 3.0 | 750 | 1.5744 | 0.359 |
| 1.5814 | 4.0 | 1000 | 1.5805 | 0.3345 |
| 1.5804 | 5.0 | 1250 | 1.5820 | 0.352 |
| 1.5762 | 6.0 | 1500 | 1.5846 | 0.352 |
| 1.5781 | 7.0 | 1750 | 1.5829 | 0.352 |
| 1.5759 | 8.0 | 2000 | 1.5813 | 0.352 |
| 1.5741 | 9.0 | 2250 | 1.5835 | 0.33 |
| 1.573 | 10.0 | 2500 | 1.5795 | 0.334 |