EuroBERT-210m-humour-detection-expanded-train

This model is a fine-tuned version of EuroBERT/EuroBERT-210m on the None dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.4609
• eval_accuracy: 0.6985
• eval_precision: 0.6288
• eval_recall: 0.9826
• eval_f1: 0.7668
• eval_runtime: 11.2227
• eval_samples_per_second: 172.864
• eval_steps_per_second: 10.871
• epoch: 1.4762
• step: 9042

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: 32
• eval_batch_size: 16
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.2
• num_epochs: 3
• mixed_precision_training: Native AMP

Framework versions

• Transformers 4.51.3
• Pytorch 2.6.0+cu124
• Datasets 3.6.0
• Tokenizers 0.21.1