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# ner_model

This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the wnut_17 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2729
- Precision: 0.6122
- Recall: 0.4306
- F1: 0.5056
- Accuracy: 0.9499

## 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: 5e-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: 3.0

### Training results



### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["wnut_17"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "distilbert-base-multilingual-cased", "model-index": [{"name": "ner_model", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "wnut_17", "type": "wnut_17", "config": "wnut_17", "split": "validation", "args": "wnut_17"}, "metrics": [{"type": "precision", "value": 0.6122448979591837, "name": "Precision"}, {"type": "recall", "value": 0.430622009569378, "name": "Recall"}, {"type": "f1", "value": 0.5056179775280899, "name": "F1"}, {"type": "accuracy", "value": 0.9499141930973114, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors distilbert token-classification generated_from_trainer dataset:wnut_17 base_model:distilbert-base-multilingual-cased license:apache-2.0 model-index autotrain_compatible endpoints_compatible has_space region:us