File size: 1,755 Bytes
58e66f1 757c5b3 58e66f1 757c5b3 58e66f1 757c5b3 58e66f1 757c5b3 58e66f1 757c5b3 58e66f1 757c5b3 58e66f1 757c5b3 58e66f1 757c5b3 58e66f1 757c5b3 58e66f1 757c5b3 58e66f1 757c5b3 58e66f1 757c5b3 58e66f1 757c5b3 58e66f1 757c5b3 58e66f1 757c5b3 58e66f1 757c5b3 58e66f1 757c5b3 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 |
---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner4invoice
results: []
---
<!-- 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-finetuned-ner4invoice
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0257
- Precision: 0.8861
- Recall: 0.9859
- F1: 0.9333
- Accuracy: 0.9945
## 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 | 0.0530 | 0.5455 | 0.5070 | 0.5255 | 0.9830 |
| No log | 2.0 | 28 | 0.0450 | 0.7654 | 0.8732 | 0.8158 | 0.9822 |
| No log | 3.0 | 42 | 0.0257 | 0.8861 | 0.9859 | 0.9333 | 0.9945 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|