bert-f1-durga-muhammad-b

This model is a fine-tuned version of google-bert/bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.0000
• eval_accuracy: 1.0
• eval_precision: 1.0
• eval_recall: 1.0
• eval_f1: 1.0
• eval_runtime: 27.3528
• eval_samples_per_second: 36.559
• eval_steps_per_second: 1.535
• epoch: 68.8095
• step: 2890

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: 24
• eval_batch_size: 24
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1000

Framework versions

• Transformers 4.44.2
• Pytorch 2.5.0+cu121
• Datasets 3.1.0
• Tokenizers 0.19.1