README.md

metadata

library_name: transformers
language:
  - en
license: apache-2.0
base_model: google/bert_uncased_L-2_H-512_A-8
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
model-index:
  - name: bert_uncased_L-2_H-512_A-8_qqp
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE QQP
          type: glue
          args: qqp
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8775166955231264
          - name: F1
            type: f1
            value: 0.8349663400653202

bert_uncased_L-2_H-512_A-8_qqp

This model is a fine-tuned version of google/bert_uncased_L-2_H-512_A-8 on the GLUE QQP dataset. It achieves the following results on the evaluation set:

• Loss: 0.2936
• Accuracy: 0.8775
• F1: 0.8350
• Combined Score: 0.8562

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	F1	Combined Score
0.3895	1.0	1422	0.3335	0.8481	0.7883	0.8182
0.3058	2.0	2844	0.3006	0.8682	0.8232	0.8457
0.26	3.0	4266	0.2964	0.8745	0.8298	0.8522
0.2254	4.0	5688	0.2936	0.8775	0.8350	0.8562
0.195	5.0	7110	0.3151	0.8803	0.8427	0.8615
0.1696	6.0	8532	0.3190	0.8815	0.8431	0.8623
0.1492	7.0	9954	0.3478	0.8781	0.8415	0.8598
0.1322	8.0	11376	0.3563	0.8823	0.8441	0.8632
0.1175	9.0	12798	0.3841	0.8835	0.8470	0.8652

Framework versions

• Transformers 4.46.3
• Pytorch 2.2.1+cu118
• Datasets 2.17.0
• Tokenizers 0.20.3