metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- ag_news
model-index:
- name: bert-base-uncased-ag-news-finetuned
results: []
bert-base-uncased-ag-news-finetuned
This model is a fine-tuned version of bert-base-uncased on the ag_news dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.2589
- eval_accuracy: 0.9424
- eval_f1(weighted): 0.9425
- eval_precision(weighted): 0.9427
- eval_recall(weighted): 0.9424
- eval_runtime: 73.6126
- eval_samples_per_second: 326.031
- eval_steps_per_second: 6.792
- epoch: 1.0
- step: 2000
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: 48
- eval_batch_size: 48
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1