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responsible_iddistilbert-base-uncased

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 2.5066
• Accuracy: 0.5215

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: 160
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 12
• total_train_batch_size: 1920
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 512.0

Training results

Framework versions

• Transformers 4.32.0
• Pytorch 2.0.1
• Datasets 2.14.4
• Tokenizers 0.13.3