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bert-base-multilingual-cased-finetuned-train

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

• eval_loss: 0.0158
• eval_accuracy: 0.9974
• eval_f1: 0.9974
• eval_runtime: 216.731
• eval_samples_per_second: 83.103
• eval_steps_per_second: 10.391
• epoch: 1.0
• step: 2252

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Framework versions

• Transformers 4.34.0.dev0
• Pytorch 2.0.0
• Datasets 2.14.5
• Tokenizers 0.13.3