README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: distilbert-base-uncased-finetuned-wnli
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: glue
          type: glue
          args: wnli
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.5492957746478874

distilbert-base-uncased-finetuned-wnli

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

• Loss: 0.6950
• Accuracy: 0.5493

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: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	40	0.6929	0.5211
No log	2.0	80	0.6951	0.4789
No log	3.0	120	0.6950	0.5493
No log	4.0	160	0.6966	0.5352
No log	5.0	200	0.6966	0.5352

Framework versions

• Transformers 4.20.1
• Pytorch 1.12.0+cu113
• Datasets 2.4.0
• Tokenizers 0.12.1