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