metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- yahoo_answers_topics
metrics:
- accuracy
model-index:
- name: topic_classification
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: yahoo_answers_topics
type: yahoo_answers_topics
config: yahoo_answers_topics
split: test
args: yahoo_answers_topics
metrics:
- name: Accuracy
type: accuracy
value: 0.6518
topic_classification
This model is a fine-tuned version of bert-base-uncased on the yahoo_answers_topics dataset. It achieves the following results on the evaluation set:
- Loss: 1.1769
- Accuracy: 0.6518
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: 0.0001
- train_batch_size: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.005 | 1.0 | 625 | 1.0478 | 0.6519 |
| 0.7717 | 2.0 | 1250 | 1.0482 | 0.6557 |
| 0.4566 | 3.0 | 1875 | 1.1769 | 0.6518 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0