fine-tuned-bertMultilingual-casedNoNeutral

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fine-tuned-bertMultilingual-casedNoNeutral

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

• eval_loss: 1.3286
• eval_accuracy: {'accuracy': 0.823321554770318}
• eval_f1score: {'f1': 0.8030371145082857}
• eval_runtime: 8.8957
• eval_samples_per_second: 31.813
• eval_steps_per_second: 4.047
• 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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 61
• num_epochs: 20

Framework versions

• Transformers 4.42.4
• Pytorch 2.3.1+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1