metadata

library_name: transformers
language:
  - en
license: apache-2.0
base_model: google/bert_uncased_L-4_H-128_A-2
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: bert_uncased_L-4_H-128_A-2_sst2
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE SST2
          type: glue
          args: sst2
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8130733944954128

bert_uncased_L-4_H-128_A-2_sst2

This model is a fine-tuned version of google/bert_uncased_L-4_H-128_A-2 on the GLUE SST2 dataset. It achieves the following results on the evaluation set:

Loss: 0.4254
Accuracy: 0.8131

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
0.497	1.0	264	0.4757	0.7787
0.3535	2.0	528	0.4270	0.8108
0.2951	3.0	792	0.4281	0.8211
0.2539	4.0	1056	0.4254	0.8131
0.2259	5.0	1320	0.4344	0.8257
0.2048	6.0	1584	0.4487	0.8314
0.1892	7.0	1848	0.4820	0.8222
0.1754	8.0	2112	0.4954	0.8349
0.1643	9.0	2376	0.4869	0.8222

Framework versions

Transformers 4.46.3
Pytorch 2.2.1+cu118
Datasets 2.17.0
Tokenizers 0.20.3