| ---
|
| library_name: peft
|
| base_model: DeepPavlov/rubert-base-cased
|
| tags:
|
| - generated_from_trainer
|
| metrics:
|
| - precision
|
| - recall
|
| - f1
|
| model-index:
|
| - name: pollen-ner-2000
|
| results: []
|
| ---
|
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # pollen-ner-2000 |
|
|
| This model is a fine-tuned version of [DeepPavlov/rubert-base-cased](https://huggingface.co/DeepPavlov/rubert-base-cased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2712 |
| - Precision: 0.7229 |
| - Recall: 0.8434 |
| - F1: 0.7785 |
|
|
| ## 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 | 250 | 0.7862 | 0.4691 | 0.0763 | 0.1313 | |
| | 1.1314 | 2.0 | 500 | 0.5175 | 0.4883 | 0.6305 | 0.5504 | |
| | 1.1314 | 3.0 | 750 | 0.4163 | 0.5199 | 0.7088 | 0.5998 | |
| | 0.6496 | 4.0 | 1000 | 0.3507 | 0.5949 | 0.7550 | 0.6655 | |
| | 0.6496 | 5.0 | 1250 | 0.3229 | 0.6238 | 0.7791 | 0.6929 | |
| | 0.51 | 6.0 | 1500 | 0.2990 | 0.6857 | 0.8193 | 0.7466 | |
| | 0.51 | 7.0 | 1750 | 0.2847 | 0.7075 | 0.8353 | 0.7661 | |
| | 0.4533 | 8.0 | 2000 | 0.2749 | 0.7133 | 0.8394 | 0.7712 | |
| | 0.4533 | 9.0 | 2250 | 0.2723 | 0.7216 | 0.8434 | 0.7778 | |
| | 0.4361 | 10.0 | 2500 | 0.2712 | 0.7229 | 0.8434 | 0.7785 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.15.2 |
| - Transformers 4.51.3 |
| - Pytorch 2.7.0+cu128 |
| - Datasets 3.5.0 |
| - Tokenizers 0.21.1 |
