README.md

metadata

license: mit
tags:
  - generated_from_trainer
datasets:
  - sst2
metrics:
  - accuracy
  - f1
model-index:
  - name: finetuning-xlm-roberta-base-on-sst2
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: sst2
          type: sst2
          config: default
          split: validation
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9220183486238532
          - name: F1
            type: f1
            value: 0.9246119733924612

finetuning-xlm-roberta-base-on-sst2

This model is a fine-tuned version of xlm-roberta-base on the sst2 dataset. It achieves the following results on the evaluation set:

• Loss: 0.2599
• Accuracy: 0.9220
• F1: 0.9246

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: 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: 1

Training results

Framework versions

• Transformers 4.28.0
• Pytorch 2.0.1+cu118
• Datasets 2.12.0
• Tokenizers 0.13.3