|
--- |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- precision |
|
- recall |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: camembert-ner-finetuned-ner |
|
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. --> |
|
|
|
# camembert-ner-finetuned-ner |
|
|
|
This model is a fine-tuned version of [Jean-Baptiste/camembert-ner](https://huggingface.co/Jean-Baptiste/camembert-ner) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1258 |
|
- Precision: 0.9791 |
|
- Recall: 0.9723 |
|
- F1: 0.9757 |
|
- Accuracy: 0.9775 |
|
|
|
## 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: 5 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
| No log | 1.0 | 219 | 0.1130 | 0.9569 | 0.9723 | 0.9645 | 0.9687 | |
|
| No log | 2.0 | 438 | 0.1681 | 0.9528 | 0.9769 | 0.9647 | 0.9646 | |
|
| 0.1656 | 3.0 | 657 | 0.1253 | 0.9693 | 0.9827 | 0.9759 | 0.9779 | |
|
| 0.1656 | 4.0 | 876 | 0.1230 | 0.9692 | 0.9804 | 0.9748 | 0.9783 | |
|
| 0.047 | 5.0 | 1095 | 0.1258 | 0.9791 | 0.9723 | 0.9757 | 0.9775 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.22.2 |
|
- Pytorch 1.12.1+cu113 |
|
- Datasets 2.5.1 |
|
- Tokenizers 0.12.1 |
|
|
