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.ipynb_checkpoints/README-checkpoint.md

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+---
+language: 
+- en
+thumbnail: https://avatars3.githubusercontent.com/u/32437151?s=460&u=4ec59abc8d21d5feea3dab323d23a5860e6996a4&v=4
+tags:
+- text-classification
+- ag_news
+- pytorch
+license: MIT
+datasets:
+- ag_news
+metrics:
+- accuracy
+---
+
+# bert-base-uncased-ag-news
+
+## Model description
+
+`bert-base-uncased` finetuned on the AG News dataset using PyTorch Lightning. Sequence length 128, learning rate 2e-5, batch size 32, 4 T4 GPUs, 4 epochs. [The code can be found here](https://github.com/nateraw/hf-text-classification)
+
+#### Limitations and bias
+
+- Not the best model...
+
+## Training data
+
+Data came from HuggingFace's `datasets` package. The data can be viewed [on nlp viewer](https://huggingface.co/nlp/viewer/?dataset=ag_news).
+
+
+## Training procedure
+
+...
+
+## Eval results
+
+...