metadata
library_name: peft
base_model: DeepPavlov/rubert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: pollen-ner-950
results: []
pollen-ner-950
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: 0.1644
- Precision: 0.8167
- Recall: 0.9036
- F1: 0.8580
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 | 119 | 0.1739 | 0.8123 | 0.9036 | 0.8555 |
| No log | 2.0 | 238 | 0.1788 | 0.7972 | 0.8996 | 0.8453 |
| No log | 3.0 | 357 | 0.1723 | 0.8141 | 0.9056 | 0.8574 |
| No log | 4.0 | 476 | 0.1644 | 0.8167 | 0.9036 | 0.8580 |
| 0.334 | 5.0 | 595 | 0.1643 | 0.8141 | 0.9056 | 0.8574 |
Framework versions
- PEFT 0.15.2
- Transformers 4.51.3
- Pytorch 2.7.0+cu128
- Datasets 3.5.0
- Tokenizers 0.21.1