metadata

license: mit
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - f1
model-index:
  - name: debertav3-finetuned-answer-polarity-2e6-newdata
    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: 0.8526968320709598

debertav3-finetuned-answer-polarity-2e6-newdata

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

Loss: 0.4009
F1: 0.8527

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-06
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: 6

Training results

Training Loss	Epoch	Step	Validation Loss	F1
No log	1.0	221	1.1820	0.2111
1.1195	2.0	442	0.7073	0.7068
0.4953	3.0	663	0.5068	0.8311
0.4953	4.0	884	0.4326	0.8498
0.2767	5.0	1105	0.4155	0.8553
0.2147	6.0	1326	0.4009	0.8527

Framework versions

Transformers 4.29.2
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3