| 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 | |
| ... |