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bert-base-mongolian-uncased-ner
tergel/bert-base-mongolian-uncased-ner
bert-base-mongolian-uncased-ner is a machine learning model from tergel. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Model type
- bert
- Access
- Public
- Created
- Aug 9, 2024
- Updated
- Aug 9, 2024
- SHA
- dd44d2ed
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. -->
bert-base-mongolian-uncased-ner
This model is a fine-tuned version of tergel/bert-base-mongolian-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1610
- Precision: 0.8207
- Recall: 0.8426
- F1: 0.8315
- Accuracy: 0.9593
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: 2e-05
- train_batch_size: 128
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.3447 | 1.0 | 60 | 0.1578 | 0.7339 | 0.7793 | 0.7559 | 0.9468 |
| 0.136 | 2.0 | 120 | 0.1348 | 0.7915 | 0.8026 | 0.7970 | 0.9545 |
| 0.0997 | 3.0 | 180 | 0.1325 | 0.8020 | 0.8288 | 0.8152 | 0.9570 |
| 0.0761 | 4.0 | 240 | 0.1351 | 0.8086 | 0.8310 | 0.8196 | 0.9584 |
| 0.0595 | 5.0 | 300 | 0.1396 | 0.8173 | 0.8334 | 0.8253 | 0.9591 |
| 0.0485 | 6.0 | 360 | 0.1455 | 0.8084 | 0.8313 | 0.8197 | 0.9576 |
| 0.0399 | 7.0 | 420 | 0.1548 | 0.8135 | 0.8377 | 0.8254 | 0.9581 |
| 0.0354 | 8.0 | 480 | 0.1586 | 0.8179 | 0.8407 | 0.8292 | 0.9587 |
| 0.0315 | 9.0 | 540 | 0.1599 | 0.8165 | 0.8414 | 0.8288 | 0.9587 |
| 0.0283 | 10.0 | 600 | 0.1610 | 0.8207 | 0.8426 | 0.8315 | 0.9593 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Type
- bert
- Languages
- mn
- Created
- Aug 9, 2024
- Updated
- Aug 9, 2024