README.md

metadata

tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: twitter-roberta-base-emotion-finetuned-wnli
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: glue
          type: glue
          config: wnli
          split: train
          args: wnli
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.5633802816901409

twitter-roberta-base-emotion-finetuned-wnli

This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-emotion on the glue dataset. It achieves the following results on the evaluation set:

• Loss: 0.6983
• Accuracy: 0.5634

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: 32
• eval_batch_size: 32
• 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	Accuracy
No log	1.0	20	0.6983	0.5634
No log	2.0	40	0.7132	0.3380
No log	3.0	60	0.7104	0.3380

Framework versions

• Transformers 4.22.2
• Pytorch 1.12.1+cu113
• Datasets 2.5.2
• Tokenizers 0.12.1