Instructions to use MayaLager/bge-small-ner-conll2003-corrupted with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MayaLager/bge-small-ner-conll2003-corrupted with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="MayaLager/bge-small-ner-conll2003-corrupted")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("MayaLager/bge-small-ner-conll2003-corrupted") model = AutoModelForTokenClassification.from_pretrained("MayaLager/bge-small-ner-conll2003-corrupted", device_map="auto") - Notebooks
- Google Colab
- Kaggle
bge-small-ner-conll2003-corrupted
This model is a fine-tuned version of BAAI/bge-small-en-v1.5 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0833
- Precision: 0.8912
- Recall: 0.9207
- F1: 0.9057
- Accuracy: 0.9805
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1515 | 1.0 | 1250 | 0.1334 | 0.8136 | 0.8718 | 0.8417 | 0.9700 |
| 0.0956 | 2.0 | 2500 | 0.0955 | 0.8669 | 0.9032 | 0.8847 | 0.9777 |
| 0.0711 | 3.0 | 3750 | 0.0843 | 0.8777 | 0.9155 | 0.8962 | 0.9793 |
| 0.0422 | 4.0 | 5000 | 0.0844 | 0.8900 | 0.9209 | 0.9052 | 0.9805 |
| 0.0328 | 5.0 | 6250 | 0.0833 | 0.8912 | 0.9207 | 0.9057 | 0.9805 |
Framework versions
- Transformers 5.18.0
- Pytorch 2.11.0+cu130
- Datasets 4.8.5
- Tokenizers 0.23.2
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Model tree for MayaLager/bge-small-ner-conll2003-corrupted
Base model
BAAI/bge-small-en-v1.5