bert-base-uncased finetuned on the emotion dataset using PyTorch Lightning. Sequence length 128, learning rate 2e-5, batch size 32, 2 GPUs, 4 epochs.
For more details, please see, the emotion dataset on nlp viewer.
- Not the best model, but it works in a pinch I guess...
- Code not available as I just hacked this together.
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Data came from HuggingFace's
datasets package. The data can be viewed on nlp viewer.
val_acc - 0.931 (useless, as this should be precision/recall/f1)
The score was calculated using PyTorch Lightning metrics.
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