pollen-ner-700

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

• Loss: 0.2056
• Precision: 0.7772
• Recall: 0.8755
• F1: 0.8234

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: 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
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1
No log	1.0	88	0.2270	0.7469	0.8594	0.7993
No log	2.0	176	0.2174	0.7611	0.8635	0.8090
No log	3.0	264	0.2216	0.7601	0.8715	0.8120
No log	4.0	352	0.2156	0.7691	0.8695	0.8162
No log	5.0	440	0.2267	0.7423	0.8735	0.8026
0.4359	6.0	528	0.2100	0.7709	0.8715	0.8181
0.4359	7.0	616	0.2118	0.7726	0.8735	0.8200
0.4359	8.0	704	0.2075	0.7717	0.8755	0.8203
0.4359	9.0	792	0.2056	0.7772	0.8755	0.8234
0.4359	10.0	880	0.2091	0.7707	0.8775	0.8207

Framework versions

• PEFT 0.15.2
• Transformers 4.51.3
• Pytorch 2.7.0+cu128
• Datasets 3.5.0
• Tokenizers 0.21.1