metadata
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner-invoice
results: []
bert-finetuned-ner-invoice
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1008
- Precision: 0.9373
- Recall: 0.8718
- F1: 0.9034
- Accuracy: 0.9812
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 35 | 0.3186 | 0.6126 | 0.6423 | 0.6271 | 0.9315 |
| No log | 2.0 | 70 | 0.1265 | 0.8946 | 0.8332 | 0.8628 | 0.9768 |
| No log | 3.0 | 105 | 0.1008 | 0.9373 | 0.8718 | 0.9034 | 0.9812 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1