---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: DistilBERT-finetuned-ner-S800
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# DistilBERT-finetuned-ner-S800

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0834
- Precision: 0.5329
- Recall: 0.6129
- F1: 0.5701
- Accuracy: 0.9689

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 55   | 0.1363          | 0.2460    | 0.2987 | 0.2698 | 0.9436   |
| No log        | 2.0   | 110  | 0.0926          | 0.3943    | 0.4656 | 0.4270 | 0.9636   |
| No log        | 3.0   | 165  | 0.0823          | 0.4937    | 0.6059 | 0.5441 | 0.9683   |
| No log        | 4.0   | 220  | 0.0802          | 0.5187    | 0.5849 | 0.5498 | 0.9696   |
| No log        | 5.0   | 275  | 0.0834          | 0.5329    | 0.6129 | 0.5701 | 0.9689   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3