README.md

metadata

license: mit
tags:
  - generated_from_trainer
datasets:
  - emotion
metrics:
  - accuracy
base_model: microsoft/deberta-v3-xsmall
model-index:
  - name: deberta-v3-xsmall-emotion
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: emotion
          type: emotion
          args: default
        metrics:
          - type: accuracy
            value: 0.932
            name: Accuracy

deberta-v3-xsmall-emotion

This model is a fine-tuned version of microsoft/deberta-v3-xsmall on the emotion dataset. It achieves the following results on the evaluation set:

• Loss: 0.1877
• Accuracy: 0.932

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: 3e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 5
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.3683	1.0	500	0.8479	0.6975
0.547	2.0	1000	0.2881	0.905
0.2378	3.0	1500	0.2116	0.925
0.1704	4.0	2000	0.1877	0.932
0.1392	5.0	2500	0.1718	0.9295

Framework versions

• Transformers 4.12.3
• Pytorch 1.9.1
• Datasets 1.15.1
• Tokenizers 0.10.3