bert-base-uncased-finetuned-imdb

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

• eval_loss: 3.0882
• eval_model_preparation_time: 0.0079
• eval_runtime: 309.0269
• eval_samples_per_second: 3.236
• eval_steps_per_second: 0.052
• epoch: 0
• step: 0

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: 64
• eval_batch_size: 64
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 3.0
• mixed_precision_training: Native AMP

Framework versions

• Transformers 5.15.0
• Pytorch 2.11.0+cpu
• Datasets 4.0.0
• Tokenizers 0.22.2