Downloads · 30 days
6
40% of all-time downloads
pollen-ner2-100
DanielNRU/pollen-ner2-100
pollen-ner2-100 is a machine learning model from DanielNRU. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft.
should probably proofread and complete it, then remove this comment. --
All-time downloads
15
Public
Repo size
2.4 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.json3.1 MB · 46%
At a glance
- Library
- peft
- Access
- Public
- Created
- May 22, 2025
- Updated
- May 22, 2025
- SHA
- 3609f13e
Base models
Model card
From the Hugging Face model README
<!-- 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-ner2-100
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: 2.0243
- Precision: 0.0057
- Recall: 0.0141
- F1: 0.0081
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 | 13 | 2.0243 | 0.0057 | 0.0141 | 0.0081 |
| No log | 2.0 | 26 | 1.7798 | 0.0034 | 0.0020 | 0.0025 |
| No log | 3.0 | 39 | 1.5304 | 0.0 | 0.0 | 0.0 |
Framework versions
- PEFT 0.15.2
- Transformers 4.51.3
- Pytorch 2.7.0+cu128
- Datasets 3.5.0
- Tokenizers 0.21.1
- Library
- peft
- Created
- May 22, 2025
- Updated
- May 22, 2025