metadata
library_name: peft
base_model: DeepPavlov/bert-base-bg-cs-pl-ru-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: pollen-ner2-700
results: []
pollen-ner2-700
This model is a fine-tuned version of DeepPavlov/bert-base-bg-cs-pl-ru-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2760
- Precision: 0.6858
- Recall: 0.7932
- F1: 0.7356
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 | 0.2763 | 0.6856 | 0.7751 | 0.7276 |
| No log | 2.0 | 176 | 0.2760 | 0.6858 | 0.7932 | 0.7356 |
| No log | 3.0 | 264 | 0.2686 | 0.6865 | 0.7871 | 0.7334 |
| No log | 4.0 | 352 | 0.2685 | 0.6799 | 0.7892 | 0.7305 |
Framework versions
- PEFT 0.15.2
- Transformers 4.51.3
- Pytorch 2.7.0+cu128
- Datasets 3.5.0
- Tokenizers 0.21.1