Text Classification
Transformers
PyTorch
ONNX
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use AdamCodd/tinybert-emotion-balanced with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AdamCodd/tinybert-emotion-balanced with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AdamCodd/tinybert-emotion-balanced")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AdamCodd/tinybert-emotion-balanced") model = AutoModelForSequenceClassification.from_pretrained("AdamCodd/tinybert-emotion-balanced") - Inference
- Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -105,8 +105,8 @@ The following hyperparameters were used during training:
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surprise 0.9016 0.9866 0.9422 1496
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accuracy 0.9355 8976
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macro avg
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weighted avg
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test_acc: 0.9354946613311768
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test_loss: 0.1809326708316803
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surprise 0.9016 0.9866 0.9422 1496
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accuracy 0.9355 8976
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macro avg 0.9370 0.9355 0.9353 8976
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weighted avg 0.9370 0.9355 0.9353 8976
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test_acc: 0.9354946613311768
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test_loss: 0.1809326708316803
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