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

gavulsim/distilbert_finetuned_yahoo_answers_topics

deberta_finetuned_yahoo_answers_topics

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

gavulsim/
distilbert_finetuned_yahoo_answers_topics