README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: BERT_Mod_3
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: glue
          type: glue
          args: mnli
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8198675496688742

BERT_Mod_3

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: 0.6760
• Accuracy: 0.8199

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: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5167	1.0	24544	0.4953	0.8077
0.414	2.0	49088	0.4802	0.8148
0.2933	3.0	73632	0.5783	0.8186
0.2236	4.0	98176	0.6760	0.8199

Framework versions

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