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metadata
library_name: transformers
language:
  - en
license: apache-2.0
base_model: google/bert_uncased_L-4_H-512_A-8
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: bert_uncased_L-4_H-512_A-8_sst2
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE SST2
          type: glue
          args: sst2
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8899082568807339

bert_uncased_L-4_H-512_A-8_sst2

This model is a fine-tuned version of google/bert_uncased_L-4_H-512_A-8 on the GLUE SST2 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3331
  • Accuracy: 0.8899

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
0.3288 1.0 264 0.3598 0.8601
0.1917 2.0 528 0.3433 0.8830
0.1386 3.0 792 0.3331 0.8899
0.108 4.0 1056 0.4032 0.8761
0.0871 5.0 1320 0.4482 0.8670
0.0734 6.0 1584 0.3767 0.8796
0.0592 7.0 1848 0.4376 0.8796
0.0509 8.0 2112 0.4948 0.8716

Framework versions

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