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

  • Loss: 2.9150
  • Accuracy: 0.2662

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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
3.0528 0.44 1000 3.0265 0.2223
2.9836 0.89 2000 2.9263 0.2332
2.7409 1.33 3000 2.9041 0.2533
2.7905 1.77 4000 2.8763 0.2606
2.4359 2.22 5000 2.9072 0.2642
2.4507 2.66 6000 2.9230 0.2644

Framework versions

  • Transformers 4.7.0.dev0
  • Pytorch 1.8.1+cu102
  • Datasets 1.8.0
  • Tokenizers 0.10.3
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Model size
82.2M params
Tensor type
I64
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F32
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Inference API
This model can be loaded on Inference API (serverless).

Dataset used to train julien-c/reactiongif-roberta