transformers tensorboard safetensors distilbert token-classification generated_from_trainer base_model:distilbert-base-cased license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ner-classifier-distil-bert
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ner-classifier-distil-bert

This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0484
- Precision: 0.9237
- Recall: 0.9388
- F1: 0.9312
- Accuracy: 0.9929

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0319        | 1.0   | 3546  | 0.0326          | 0.8726    | 0.9023 | 0.8872 | 0.9882   |
| 0.0206        | 2.0   | 7092  | 0.0285          | 0.8967    | 0.9273 | 0.9117 | 0.9910   |
| 0.0133        | 3.0   | 10638 | 0.0295          | 0.9072    | 0.9307 | 0.9188 | 0.9916   |
| 0.0081        | 4.0   | 14184 | 0.0327          | 0.9127    | 0.9274 | 0.9200 | 0.9918   |
| 0.0038        | 5.0   | 17730 | 0.0346          | 0.9205    | 0.9297 | 0.9251 | 0.9922   |
| 0.0044        | 6.0   | 21276 | 0.0376          | 0.9258    | 0.9299 | 0.9278 | 0.9925   |
| 0.0017        | 7.0   | 24822 | 0.0427          | 0.9277    | 0.9256 | 0.9266 | 0.9923   |
| 0.0038        | 8.0   | 28368 | 0.0460          | 0.9170    | 0.9399 | 0.9283 | 0.9926   |
| 0.0008        | 9.0   | 31914 | 0.0473          | 0.9266    | 0.9344 | 0.9305 | 0.9928   |
| 0.0026        | 10.0  | 35460 | 0.0484          | 0.9237    | 0.9388 | 0.9312 | 0.9929   |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
