README.md

metadata

license: apache-2.0
base_model: odunola/bert-base-uncased-ag-news-finetuned
tags:
  - generated_from_trainer
datasets:
  - ag_news
metrics:
  - accuracy
model-index:
  - name: bert-base-uncased-ag-news-finetuned-2
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: ag_news
          type: ag_news
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9819166666666667

bert-base-uncased-ag-news-finetuned-2

This model is a fine-tuned version of odunola/bert-base-uncased-ag-news-finetuned on the ag_news dataset. It achieves the following results on the evaluation set:

• Loss: 0.0712
• Accuracy: 0.9819
• F1(weighted): 0.9819
• Precision(weighted): 0.9819
• Recall(weighted): 0.9819

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: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1(weighted)	Precision(weighted)	Recall(weighted)
0.1006	1.0	6000	0.0712	0.9819	0.9819	0.9819	0.9819

Framework versions

• Transformers 4.35.0
• Pytorch 2.1.0+cu118
• Datasets 2.14.6
• Tokenizers 0.14.1