README.md

metadata

license: mit
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - f1
model-index:
  - name: deberta-finetuned-answer-polarity-warmup-f1
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: glue
          type: glue
          config: answer_pol
          split: validation
          args: answer_pol
        metrics:
          - name: F1
            type: f1
            value: 0.8602499021892139

deberta-finetuned-answer-polarity-warmup-f1

This model is a fine-tuned version of microsoft/deberta-large on the glue dataset. It achieves the following results on the evaluation set:

• Loss: 0.3748
• F1: 0.8602

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: 7e-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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	F1
No log	1.0	364	0.5669	0.8303
0.0791	2.0	728	0.5405	0.4630
0.3408	3.0	1092	0.3748	0.8602

Framework versions

• Transformers 4.29.2
• Pytorch 2.0.1+cu118
• Datasets 2.12.0
• Tokenizers 0.13.3