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# RISE_NER4

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1028
- Precision: 0.8937
- Recall: 0.9059
- F1: 0.8997
- Accuracy: 0.9834

## 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: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.012         | 1.0   | 16410 | 0.0639          | 0.8898    | 0.8978 | 0.8938 | 0.9827   |
| 0.0074        | 2.0   | 32820 | 0.0788          | 0.9006    | 0.8950 | 0.8978 | 0.9831   |
| 0.003         | 3.0   | 49230 | 0.0930          | 0.8938    | 0.9012 | 0.8975 | 0.9831   |
| 0.0014        | 4.0   | 65640 | 0.1028          | 0.8937    | 0.9059 | 0.8997 | 0.9834   |


### Framework versions

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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "RISE_NER4", "results": []}]}
transformers tensorboard safetensors distilbert token-classification generated_from_trainer base_model:distilbert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us