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---
license: mit
base_model: bert-base-cased
tags:
- CENIA
- News
metrics:
- accuracy
model-index:
- name: bert-base-cased-finetuned
results: []
datasets:
- cmunhozc/usa_news_en
language:
- en
pipeline_tag: text-classification
widget:
- text: "Pfizer CEO tests positive for COVID-19, has mild symptoms || DHS Secretary Alejandro Mayorkas tests positive for COVID-19, reports mild symptoms"
output:
- label: RELATED
score: 0.2
- label: UNRELATED
score: 0.8
- text: "California’s most destructive earthquakes || Deadly and destructive California earthquakes with images from The San Francisco Chronicle’s archive."
output:
- label: RELATED
score: 0.8
- label: UNRELATED
score: 0.1
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-base-cased-finetuned
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the "cmunhozc/usa_news_en" train dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0900
- Accuracy: 0.9800
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0967 | 1.0 | 3526 | 0.0651 | 0.9771 |
| 0.0439 | 2.0 | 7052 | 0.0820 | 0.9776 |
| 0.0231 | 3.0 | 10578 | 0.0900 | 0.9800 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0 |