dair-ai/emotion
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How to use gokuls/add-bert-emotion_48 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="gokuls/add-bert-emotion_48") # Load model directly
from transformers import AutoModelForSequenceClassification
model = AutoModelForSequenceClassification.from_pretrained("gokuls/add-bert-emotion_48", dtype="auto")This model is a fine-tuned version of gokuls/add_bert_12_layer_model_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 |
|---|---|---|---|---|
| 1.5242 | 1.0 | 250 | 1.4118 | 0.486 |
| 1.2805 | 2.0 | 500 | 1.1681 | 0.5735 |
| 1.0331 | 3.0 | 750 | 0.9456 | 0.637 |
| 0.805 | 4.0 | 1000 | 0.7158 | 0.782 |
| 0.5252 | 5.0 | 1250 | 0.5216 | 0.8345 |
| 0.4039 | 6.0 | 1500 | 0.4079 | 0.8685 |
| 0.3299 | 7.0 | 1750 | 0.4040 | 0.873 |
| 0.2692 | 8.0 | 2000 | 0.3403 | 0.8855 |
| 0.218 | 9.0 | 2250 | 0.3382 | 0.8865 |
| 0.1812 | 10.0 | 2500 | 0.3536 | 0.887 |