glue_sst_classifier / README.md
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - nyu-mll/glue
metrics:
  - f1
  - accuracy
base_model: bert-base-cased
model-index:
  - name: glue_sst_classifier
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: glue
          type: glue
          args: sst2
        metrics:
          - type: f1
            value: 0.9033707865168539
            name: F1
          - type: accuracy
            value: 0.9013761467889908
            name: Accuracy

glue_sst_classifier

This model is a fine-tuned version of bert-base-cased on the glue dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2359
  • F1: 0.9034
  • Accuracy: 0.9014

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: 1e-05
  • train_batch_size: 128
  • eval_batch_size: 128
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 1.0

Training results

Training Loss Epoch Step Validation Loss F1 Accuracy
0.3653 0.19 100 0.3213 0.8717 0.8727
0.291 0.38 200 0.2662 0.8936 0.8911
0.2239 0.57 300 0.2417 0.9081 0.9060
0.2306 0.76 400 0.2359 0.9105 0.9094
0.2185 0.95 500 0.2371 0.9011 0.8991

Framework versions

  • Transformers 4.18.0
  • Pytorch 1.11.0+cu113
  • Datasets 2.1.0
  • Tokenizers 0.12.1