dair-ai/emotion
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How to use potradovec/minisss with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="potradovec/minisss") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("potradovec/minisss")
model = AutoModelForSequenceClassification.from_pretrained("potradovec/minisss")This model is a fine-tuned version of microsoft/MiniLM-L12-H384-uncased 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 | F1 |
|---|---|---|---|---|
| 1.1818 | 1.0 | 250 | 0.8298 | 0.5948 |
| 0.6392 | 2.0 | 500 | 0.3998 | 0.9005 |
| 0.3246 | 3.0 | 750 | 0.2472 | 0.9301 |
| 0.2151 | 4.0 | 1000 | 0.1937 | 0.9341 |
| 0.1707 | 5.0 | 1250 | 0.1791 | 0.9361 |
Base model
microsoft/MiniLM-L12-H384-uncased