metadata
license: apache-2.0
base_model: distilbert-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: 0.7125166666666667
topic_classification
This model is a fine-tuned version of distilbert-base-uncased on the yahoo_answers_topics dataset. It achieves the following results on the evaluation set:
- Loss: 0.9119
- Accuracy: 0.7125
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 30000
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.0187 | 0.0286 | 5000 | 1.0647 | 0.6695 |
| 0.9944 | 0.0571 | 10000 | 1.0281 | 0.6782 |
| 0.9641 | 0.0857 | 15000 | 0.9694 | 0.6969 |
| 0.8833 | 0.1143 | 20000 | 0.9426 | 0.7045 |
| 0.9416 | 0.1429 | 25000 | 0.9239 | 0.7093 |
| 0.932 | 0.1714 | 30000 | 0.9119 | 0.7125 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1