---
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: 0.0797
- Precision: 0.5276
- Recall: 0.6297
- F1: 0.5742
- Accuracy: 0.9700

## 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   | 0.1312          | 0.3091    | 0.3759 | 0.3392 | 0.9464   |
| No log        | 2.0   | 110  | 0.0918          | 0.4431    | 0.4965 | 0.4683 | 0.9663   |
| No log        | 3.0   | 165  | 0.0826          | 0.4836    | 0.6199 | 0.5433 | 0.9684   |
| No log        | 4.0   | 220  | 0.0777          | 0.5189    | 0.6157 | 0.5632 | 0.9703   |
| No log        | 5.0   | 275  | 0.0797          | 0.5276    | 0.6297 | 0.5742 | 0.9700   |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3