dair-ai/emotion
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How to use gokuls/hbertv1-emotion-intermediate_KD_new_2 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_2") # Load model directly
from transformers import AutoModelForSequenceClassification
model = AutoModelForSequenceClassification.from_pretrained("gokuls/hbertv1-emotion-intermediate_KD_new_2", device_map="auto")This model is a fine-tuned version of gokuls/HBERTv1_48_L10_H768_A12 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 |
|---|---|---|---|---|
| 2.954 | 1.0 | 250 | 1.8290 | 0.8255 |
| 1.775 | 2.0 | 500 | 1.6132 | 0.8285 |
| 1.5532 | 3.0 | 750 | 1.4540 | 0.8515 |
| 1.4101 | 4.0 | 1000 | 1.3212 | 0.8855 |
| 1.3138 | 5.0 | 1250 | 1.2489 | 0.8935 |
| 1.2434 | 6.0 | 1500 | 1.2280 | 0.896 |
| 1.1933 | 7.0 | 1750 | 1.2346 | 0.897 |
| 1.1417 | 8.0 | 2000 | 1.2159 | 0.8835 |
| 1.0954 | 9.0 | 2250 | 1.2792 | 0.8855 |
| 1.056 | 10.0 | 2500 | 1.2294 | 0.8875 |
| 1.0235 | 11.0 | 2750 | 1.2474 | 0.883 |
| 0.9943 | 12.0 | 3000 | 1.2179 | 0.886 |
Base model
gokuls/HBERTv1_48_L10_H768_A12