Hugging Face's logo

transformersbook
/
bert-base-uncased-issues-128

Fill-Mask
Transformers
PyTorch
bert
Generated from Trainer
Inference Endpoints
Model card Files Community
2
bert-base-uncased-issues-128 / README.md
lvwerra's picture
lvwerra HF staff
Update README.md
235bf67
preview code
|
raw
history blame contribute delete
2.39 kB
metadata
license: apache-2.0
tags:
  - generated_from_trainer
model-index:
  - name: bert-base-uncased-issues-128
    results: []

bert-base-uncased-issues-128

This model is a fine-tuned version of bert-base-uncased on the GitHub issues dataset. The model is used in Chapter 9: Dealing with Few to No Labels in the NLP with Transformers book. You can find the full code in the accompanying Github repository.

It achieves the following results on the evaluation set:

  • Loss: 1.2520

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: 32
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 16

Training results

Training Loss Epoch Step Validation Loss
2.0949 1.0 291 1.7072
1.649 2.0 582 1.4409
1.4835 3.0 873 1.4099
1.3938 4.0 1164 1.3858
1.3326 5.0 1455 1.2004
1.2949 6.0 1746 1.2955
1.2451 7.0 2037 1.2682
1.1992 8.0 2328 1.1938
1.1784 9.0 2619 1.1686
1.1397 10.0 2910 1.2050
1.1293 11.0 3201 1.2058
1.1006 12.0 3492 1.1680
1.0835 13.0 3783 1.2414
1.0757 14.0 4074 1.1522
1.062 15.0 4365 1.1176
1.0535 16.0 4656 1.2520

Framework versions

  • Transformers 4.11.3
  • Pytorch 1.10.0+cu102
  • Datasets 1.13.0
  • Tokenizers 0.10.3