bert-base-uncased-emotion / README.md
language: - en thumbnail: >- https://avatars3.githubusercontent.com/u/32437151?s=460&u=4ec59abc8d21d5feea3dab323d23a5860e6996a4&v=4 tags: - text-classification - emotion - pytorch license: apache-2.0 datasets: - emotion metrics: - accuracy
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.
Limitations and bias
- Not the best model, but it works in a pinch I guess...
- Code not available as I just hacked this together.
- Follow me on github to get notified when code is made available.
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.