Training Complete
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README.md
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---
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license: apache-2.0
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base_model: odunola/bert-base-uncased-ag-news-finetuned
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tags:
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- generated_from_trainer
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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: bert-base-uncased-ag-news-finetuned-2
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results:
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- task:
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name: Text Classification
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type: 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: train
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args: default
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9819166666666667
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# bert-base-uncased-ag-news-finetuned-2
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This model is a fine-tuned version of [odunola/bert-base-uncased-ag-news-finetuned](https://huggingface.co/odunola/bert-base-uncased-ag-news-finetuned) on the ag_news dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0712
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- Accuracy: 0.9819
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- F1(weighted): 0.9819
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- Precision(weighted): 0.9819
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- Recall(weighted): 0.9819
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1(weighted) | Precision(weighted) | Recall(weighted) |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------------:|:-------------------:|:----------------:|
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| 0.1006 | 1.0 | 6000 | 0.0712 | 0.9819 | 0.9819 | 0.9819 | 0.9819 |
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### Framework versions
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- Transformers 4.35.0
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- Pytorch 2.1.0+cu118
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- Datasets 2.14.6
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- Tokenizers 0.14.1
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