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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: 0.1411
- Precision: 0.8936
- Recall: 0.9277
- F1: 0.9103
## 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 | 0.1378 | 0.8859 | 0.9197 | 0.9025 |
| 0.15 | 2.0 | 500 | 0.1402 | 0.8917 | 0.9257 | 0.9084 |
| 0.15 | 3.0 | 750 | 0.1395 | 0.8793 | 0.9217 | 0.9 |
| 0.1469 | 4.0 | 1000 | 0.1411 | 0.8936 | 0.9277 | 0.9103 |
| 0.1469 | 5.0 | 1250 | 0.1420 | 0.8889 | 0.9317 | 0.9098 |
| 0.1463 | 6.0 | 1500 | 0.1429 | 0.8836 | 0.9297 | 0.9061 |
### Framework versions
- PEFT 0.15.2
- Transformers 4.51.3
- Pytorch 2.7.0+cu128
- Datasets 3.5.0
- Tokenizers 0.21.1 |