| license: mit | |
| tags: | |
| - generated_from_trainer | |
| model-index: | |
| - name: camembert-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 | |
| This model is a fine-tuned version of [Jean-Baptiste/camembert-ner](https://huggingface.co/Jean-Baptiste/camembert-ner) on the None dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.1179 | |
| - Overall Precision: 0.7367 | |
| - Overall Recall: 0.7522 | |
| - Overall F1: 0.7444 | |
| - Overall Accuracy: 0.9728 | |
| - Humanprod F1: 0.1639 | |
| - Loc F1: 0.7657 | |
| - Org F1: 0.5352 | |
| - Per F1: 0.7961 | |
| ## 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: 32 | |
| - eval_batch_size: 32 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 2 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Humanprod F1 | Loc F1 | Org F1 | Per F1 | | |
| |:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:------------:|:------:|:------:|:------:| | |
| | No log | 1.0 | 307 | 0.1254 | 0.7185 | 0.7420 | 0.7300 | 0.9715 | 0.0357 | 0.7579 | 0.5052 | 0.7778 | | |
| | 0.1195 | 2.0 | 614 | 0.1179 | 0.7367 | 0.7522 | 0.7444 | 0.9728 | 0.1639 | 0.7657 | 0.5352 | 0.7961 | | |
| ### Framework versions | |
| - Transformers 4.25.1 | |
| - Pytorch 1.7.1+cpu | |
| - Datasets 2.7.1 | |
| - Tokenizers 0.13.2 | |