metadata
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner4invoice12
results: []
bert-finetuned-ner4invoice12
This model is a fine-tuned version of bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2330
- Precision: 0.1905
- Recall: 0.2609
- F1: 0.2202
- Accuracy: 0.9241
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: 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 | 14 | 0.5105 | 0.0 | 0.0 | 0.0 | 0.8892 |
| No log | 2.0 | 28 | 0.2856 | 0.0566 | 0.0652 | 0.0606 | 0.9234 |
| No log | 3.0 | 42 | 0.2330 | 0.1905 | 0.2609 | 0.2202 | 0.9241 |
Framework versions
- Transformers 4.42.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1