---
base_model: distilbert/distilroberta-base
tags:
- generated_from_keras_callback
model-index:
- name: marksusol/distilroberta-base-finetuned-ner
  results: []
---

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# marksusol/distilroberta-base-finetuned-ner

This model is a fine-tuned version of [distilbert/distilroberta-base](https://huggingface.co/distilbert/distilroberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0050
- Validation Loss: 0.0060
- Train Precision: 0.9435
- Train Recall: 0.9716
- Train F1: 0.9705
- Train Accuracy: 0.9988
- Epoch: 2

## 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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 1686, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
|:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
| 0.0643     | 0.0085          | 0.9223          | 0.9608       | 0.9593   | 0.9984         | 0     |
| 0.0066     | 0.0072          | 0.9303          | 0.9707       | 0.9690   | 0.9985         | 1     |
| 0.0050     | 0.0060          | 0.9435          | 0.9716       | 0.9705   | 0.9988         | 2     |


### Framework versions

- Transformers 4.38.2
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2