eurobert_agent_queries

This model is a fine-tuned version of EuroBERT/EuroBERT-210m on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.1424
• Accuracy: 0.9445
• Precision: 0.9375
• Recall: 0.9529
• F1: 0.9452

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: 3.6e-05
• train_batch_size: 25
• eval_batch_size: 25
• 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: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 1.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.3306	0.2470	500	0.3166	0.8792	0.9020	0.8521	0.8763
0.2332	0.4941	1000	0.2144	0.9104	0.94	0.8775	0.9077
0.1929	0.7411	1500	0.1793	0.9291	0.9410	0.9164	0.9285
0.1643	0.9881	2000	0.1424	0.9445	0.9375	0.9529	0.9452

Framework versions

• Transformers 4.56.1
• Pytorch 2.4.1+cu124
• Datasets 3.6.0
• Tokenizers 0.22.0