Edit model card

mdeberta-v3-base_amazon-massive_intent

This model is a fine-tuned version of microsoft/mdeberta-v3-base on the MASSIVE1.1 dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1661
  • Accuracy: 0.8136
  • F1: 0.8136

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: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
3.6412 1.0 720 2.7536 0.3123 0.3123
2.8575 2.0 1440 1.8556 0.5303 0.5303
1.7284 3.0 2160 1.3758 0.6699 0.6699
1.3794 4.0 2880 1.1221 0.7236 0.7236
0.942 5.0 3600 0.9936 0.7609 0.7609
0.7672 6.0 4320 0.9411 0.7727 0.7727
0.602 7.0 5040 0.9196 0.7841 0.7841
0.4776 8.0 5760 0.9328 0.7895 0.7895
0.4347 9.0 6480 0.9602 0.7860 0.7860
0.2941 10.0 7200 0.9543 0.7949 0.7949
0.2783 11.0 7920 0.9979 0.8013 0.8013
0.2038 12.0 8640 0.9702 0.8062 0.8062
0.1827 13.0 9360 1.0121 0.8106 0.8106
0.1352 14.0 10080 1.0339 0.8136 0.8136
0.1115 15.0 10800 1.1091 0.8057 0.8057
0.0996 16.0 11520 1.1134 0.8151 0.8151
0.0837 17.0 12240 1.1288 0.8160 0.8160
0.0711 18.0 12960 1.1499 0.8155 0.8155
0.0594 19.0 13680 1.1622 0.8126 0.8126
0.0569 20.0 14400 1.1661 0.8136 0.8136

Framework versions

  • Transformers 4.24.0
  • Pytorch 1.12.1+cu113
  • Datasets 2.7.1
  • Tokenizers 0.13.2
Downloads last month
18
Safetensors
Model size
279M params
Tensor type
I64
·
F32
·

Finetuned from

Dataset used to train cartesinus/mdeberta-v3-base_amazon-massive_intent

Evaluation results