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roberta-large-finetuned-winogrande
This model is a fine-tuned version of roberta-large on the None dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.6939
- eval_accuracy: 0.5036
- eval_runtime: 392.378
- eval_samples_per_second: 3.229
- eval_steps_per_second: 0.808
- epoch: 1.01
- step: 1169
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 11262
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 4000
- num_epochs: 8
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cpu
- Datasets 2.10.1
- Tokenizers 0.13.2