output

This model is a fine-tuned version of google-bert/bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.7458
• Memory Allocated (gb): 2.37
• Max Memory Allocated (gb): 2.78
• Total Memory Available (gb): 94.62

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: 1
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
• lr_scheduler_type: reduce_lr_on_plateau
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 4

Training results

Framework versions

• Transformers 4.40.2
• Pytorch 2.3.1a0+git4989238
• Datasets 2.19.1
• Tokenizers 0.19.1