README.md

metadata

license: mit
base_model: roberta-base
tags:
  - generated_from_trainer
datasets:
  - RobZamp/sick
metrics:
  - accuracy
model-index:
  - name: roberta-base-fp-sick
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: sick
          type: RobZamp/sick
          config: default
          split: validation
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8787878787878788

roberta-base-fp-sick

This model is a fine-tuned version of roberta-base on the sick dataset. It achieves the following results on the evaluation set:

• Loss: 0.3257
• Accuracy: 0.8788

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: 64
• eval_batch_size: 32
• seed: 59
• 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	70	0.3581	0.8768
No log	2.0	140	0.3995	0.8465
No log	3.0	210	0.3257	0.8788

Framework versions

• Transformers 4.35.2
• Pytorch 2.0.1+cu118
• Datasets 2.15.0
• Tokenizers 0.15.0