--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer datasets: - yahoo_answers_topics metrics: - accuracy model-index: - name: deberta_finetuned_yahoo_answers_topics 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: 0.71195 --- # deberta_finetuned_yahoo_answers_topics 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: 0.9096 - Accuracy: 0.7119 ## 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 | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 1.1025 | 0.03 | 5000 | 1.0702 | 0.6717 | | 1.0132 | 0.06 | 10000 | 0.9976 | 0.6834 | | 0.8688 | 0.09 | 15000 | 0.9770 | 0.6961 | | 0.9964 | 0.11 | 20000 | 0.9356 | 0.7020 | | 0.9338 | 0.14 | 25000 | 0.9259 | 0.7090 | | 0.9059 | 0.17 | 30000 | 0.9096 | 0.7119 | ### Framework versions - Transformers 4.34.1 - Pytorch 2.1.0+cu118 - Datasets 2.14.6 - Tokenizers 0.14.1