Edit model card

mbert-quoref

This model is a fine-tuned version of bert-base-multilingual-cased on the quoref dataset. It achieves the following results on the evaluation set:

  • Loss: 3.7567

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: 10

Training results

Training Loss Epoch Step Validation Loss
1.8761 1.0 1213 1.7360
1.305 2.0 2426 1.6877
0.9271 3.0 3639 1.8559
0.6565 4.0 4852 2.0420
0.4911 5.0 6065 2.3335
0.3468 6.0 7278 2.6380
0.2522 7.0 8491 2.8952
0.2001 8.0 9704 3.2514
0.1501 9.0 10917 3.5567
0.1314 10.0 12130 3.7567

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.14.1
Downloads last month
12
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for intanm/mbert-quoref

Finetuned
(511)
this model
Finetunes
2 models

Dataset used to train intanm/mbert-quoref