itsbilal90/distilbert-base-uncased-ner-finer
By itsbilal90 · ↓ 14 · ♥ 0 · Updated 2025-01-24
What's in this repo
This page lists the files in itsbilal90/distilbert-base-uncased-ner-finer, including model.onnx.
- 1 ONNX models (.onnx files)
- 14 files, including 4 .json, 1 .md, 1 .onnx, 1 .safetensors, 1 .1, 1 .2
- Last updated 2025-01-24
ONNX files
| File | Size | Download |
|---|---|---|
| model.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
distilbert-base-uncased-ner-finer
Model description
This model is a fine-tuned version of distilbert-base-uncased on the Finer-139 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0293
- Precision: 0.8768
- Recall: 0.9064
- F1: 0.8914
- Accuracy: 0.9901
Training and evaluation data
The training data consists of the top 4 ner_tags having the most occurence from the Finer-139 dataset plus the outside tag "O".
Training results
| Epoch | Training Loss | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|
| 1 | 0.035700 | 0.035880 | 0.847873 | 0.890125 | 0.868486 | 0.987242 |
| 2 | 0.023700 | 0.029618 | 0.867055 | 0.906431 | 0.886306 | 0.989505 |
| 3 | 0.017000 | 0.029322 | 0.876898 | 0.906431 | 0.891420 | 0.990180 |
Valiadtion results
| ner_tag | precision | recall | f1-score | support |
|---|---|---|---|---|
| O | 1.00 | 0.99 | 1.00 | 229573 |
| I-DebtInstrumentInterestRateStatedPercentage | 0.94 | 0.94 | 0.94 | 5412 |
| I-LineOfCreditFacilityMaximumBorrowingCapacity | 0.82 | 0.88 | 0.85 | 4288 |
| I-DebtInstrumentBasisSpreadOnVariableRate1 | 0.89 | 0.97 | 0.93 | 4788 |
| I-DebtInstrumentFaceAmount | 0.79 | 0.76 | 0.78 | 3398 |
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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: 3
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
Model info
Created: 2025-01-23
Updated: 2025-01-24
View on Hugging FaceFiles (14)
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