Edit model card

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
Downloads last month
10
Safetensors
Model size
109M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for odunola/bert-base-uncased-ag-news-finetuned-2

Dataset used to train odunola/bert-base-uncased-ag-news-finetuned-2

Evaluation results