herbert-large-cased

This model is a fine-tuned version of allegro/herbert-large-cased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.6984
• Accuracy: 0.188

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: 5e-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: 20

Training results

Framework versions

• Transformers 4.39.3
• Pytorch 1.11.0a0+17540c5
• Datasets 2.20.0
• Tokenizers 0.15.2