metadata

library_name: transformers
language:
  - en
license: apache-2.0
base_model: google/bert_uncased_L-2_H-256_A-4
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: bert_uncased_L-2_H-256_A-4_wnli
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE WNLI
          type: glue
          args: wnli
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.5211267605633803

bert_uncased_L-2_H-256_A-4_wnli

This model is a fine-tuned version of google/bert_uncased_L-2_H-256_A-4 on the GLUE WNLI dataset. It achieves the following results on the evaluation set:

Loss: 0.6966
Accuracy: 0.5211

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: 256
eval_batch_size: 256
seed: 10
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7188	1.0	3	0.7157	0.4085
0.6947	2.0	6	0.6966	0.5211
0.693	3.0	9	0.6977	0.5352
0.699	4.0	12	0.7026	0.5493
0.6941	5.0	15	0.7084	0.3944
0.6908	6.0	18	0.7167	0.3380
0.6915	7.0	21	0.7230	0.3239

Framework versions

Transformers 4.46.3
Pytorch 2.2.1+cu118
Datasets 2.17.0
Tokenizers 0.20.3