--- 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](https://huggingface.co/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