gavulsim/distilbert_finetuned_yahoo_answers_topics

deberta_finetuned_yahoo_answers_topics

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: 0.9096
• 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