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--- |
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language: |
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- en |
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thumbnail: https://avatars3.githubusercontent.com/u/32437151?s=460&u=4ec59abc8d21d5feea3dab323d23a5860e6996a4&v=4 |
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tags: |
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- text-classification |
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- ag_news |
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- pytorch |
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license: mit |
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datasets: |
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- ag_news |
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metrics: |
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- accuracy |
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model-index: |
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- name: nateraw/bert-base-uncased-ag-news |
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results: |
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- task: |
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type: text-classification |
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name: Text Classification |
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dataset: |
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name: ag_news |
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type: ag_news |
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config: default |
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split: test |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9414473684210526 |
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verified: true |
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- name: Precision Macro |
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type: precision |
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value: 0.9416084922682436 |
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verified: true |
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- name: Precision Micro |
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type: precision |
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value: 0.9414473684210526 |
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verified: true |
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- name: Precision Weighted |
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type: precision |
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value: 0.9416084922682435 |
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verified: true |
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- name: Recall Macro |
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type: recall |
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value: 0.9414473684210527 |
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verified: true |
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- name: Recall Micro |
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type: recall |
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value: 0.9414473684210526 |
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verified: true |
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- name: Recall Weighted |
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type: recall |
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value: 0.9414473684210526 |
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verified: true |
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- name: F1 Macro |
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type: f1 |
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value: 0.9414706154045142 |
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verified: true |
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- name: F1 Micro |
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type: f1 |
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value: 0.9414473684210526 |
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verified: true |
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- name: F1 Weighted |
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type: f1 |
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value: 0.9414706154045143 |
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verified: true |
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- name: loss |
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type: loss |
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value: 0.17173650860786438 |
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verified: true |
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--- |
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# bert-base-uncased-ag-news |
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## Model description |
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`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) |
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#### Limitations and bias |
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- Not the best model... |
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## Training data |
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Data came from HuggingFace's `datasets` package. The data can be viewed [on nlp viewer](https://huggingface.co/nlp/viewer/?dataset=ag_news). |
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## Training procedure |
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... |
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## Eval results |
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... |