metrics: | |
- precision | |
- recall | |
- f1 | |
- accuracy | |
model-index: | |
- name: gunghio/distilbert-base-multilingual-cased-finetuned-conll2003-ner | |
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# gunghio/distilbert-base-multilingual-cased-finetuned-conll2003-ner | |
This model was trained from scratch on an unkown dataset. | |
It achieves the following results on the evaluation set: | |
- Loss: 0.0388 | |
- Precision: 0.9360 | |
- Recall: 0.9458 | |
- F1: 0.9409 | |
- Accuracy: 0.9902 | |
## 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 | | |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | |
| 0.1653 | 1.0 | 878 | 0.0465 | 0.9267 | 0.9300 | 0.9283 | 0.9883 | | |
| 0.0322 | 2.0 | 1756 | 0.0404 | 0.9360 | 0.9431 | 0.9396 | 0.9897 | | |
| 0.0185 | 3.0 | 2634 | 0.0388 | 0.9360 | 0.9458 | 0.9409 | 0.9902 | | |
### Framework versions | |
- Transformers 4.6.1 | |
- Pytorch 1.8.1+cu101 | |
- Datasets 1.6.2 | |
- Tokenizers 0.10.2 | |