multibert1110_lrate5b16

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

  • Loss: 0.5618
  • Precisions: 0.8632
  • Recall: 0.8248
  • F-measure: 0.8416
  • Accuracy: 0.9160

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: 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: 14

Training results

Training Loss Epoch Step Validation Loss Precisions Recall F-measure Accuracy
0.5858 1.0 236 0.3670 0.8368 0.6841 0.7038 0.8774
0.302 2.0 472 0.3603 0.8064 0.7589 0.7780 0.8931
0.1746 3.0 708 0.3442 0.8616 0.7693 0.7773 0.9026
0.118 4.0 944 0.4355 0.8683 0.7908 0.8197 0.9039
0.0822 5.0 1180 0.4320 0.8775 0.8042 0.8343 0.9094
0.0597 6.0 1416 0.4654 0.8722 0.8075 0.8298 0.9089
0.0363 7.0 1652 0.5211 0.8768 0.7803 0.8192 0.9054
0.0258 8.0 1888 0.4996 0.8631 0.8111 0.8306 0.9133
0.0165 9.0 2124 0.6172 0.8984 0.7691 0.8095 0.9073
0.0135 10.0 2360 0.5919 0.8912 0.7948 0.8312 0.9130
0.0111 11.0 2596 0.5726 0.8704 0.8003 0.8280 0.9143
0.0079 12.0 2832 0.5618 0.8632 0.8248 0.8416 0.9160
0.0047 13.0 3068 0.5917 0.8674 0.7977 0.8269 0.9149
0.0042 14.0 3304 0.5886 0.8685 0.8014 0.8292 0.9161

Framework versions

  • Transformers 4.34.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.14.1
Downloads last month
22
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 Tommert25/multibert1110_lrate5b16

Finetuned
(1629)
this model