
<!-- 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. -->

# distilbert-base-multilingual-cased-ner-demo

This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1513
- Precision: 0.8756
- Recall: 0.8973
- F1: 0.8863
- Accuracy: 0.9708

## 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: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2113        | 1.0   | 477  | 0.1338          | 0.7811    | 0.8425 | 0.8107 | 0.9562   |
| 0.1028        | 2.0   | 954  | 0.1159          | 0.8367    | 0.8670 | 0.8515 | 0.9636   |
| 0.0683        | 3.0   | 1431 | 0.1117          | 0.8552    | 0.8824 | 0.8686 | 0.9671   |
| 0.0482        | 4.0   | 1908 | 0.1215          | 0.8608    | 0.8880 | 0.8742 | 0.9682   |
| 0.0331        | 5.0   | 2385 | 0.1243          | 0.8641    | 0.8919 | 0.8778 | 0.9687   |
| 0.0251        | 6.0   | 2862 | 0.1304          | 0.8629    | 0.8901 | 0.8763 | 0.9687   |
| 0.0187        | 7.0   | 3339 | 0.1383          | 0.8695    | 0.8976 | 0.8833 | 0.9702   |
| 0.0126        | 8.0   | 3816 | 0.1489          | 0.8749    | 0.8971 | 0.8859 | 0.9700   |
| 0.0102        | 9.0   | 4293 | 0.1515          | 0.8705    | 0.8961 | 0.8831 | 0.9700   |
| 0.0082        | 10.0  | 4770 | 0.1513          | 0.8756    | 0.8973 | 0.8863 | 0.9708   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"language": ["mn"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "distilbert-base-multilingual-cased", "model-index": [{"name": "distilbert-base-multilingual-cased-ner-demo", "results": []}]}
transformers tensorboard safetensors distilbert token-classification generated_from_trainer mn base_model:distilbert-base-multilingual-cased license:apache-2.0 autotrain_compatible endpoints_compatible region:us