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

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# DistilBERT-finetuned-ner-copious

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: 0.0755
- Precision: 0.6056
- Recall: 0.6565
- F1: 0.6300
- Accuracy: 0.9752

## 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   | 63   | 0.1322          | 0.3129    | 0.2884 | 0.3002 | 0.9529   |
| No log        | 2.0   | 126  | 0.0842          | 0.5190    | 0.5739 | 0.5451 | 0.9711   |
| No log        | 3.0   | 189  | 0.0772          | 0.5765    | 0.6174 | 0.5962 | 0.9740   |
| No log        | 4.0   | 252  | 0.0751          | 0.6035    | 0.6464 | 0.6242 | 0.9751   |
| No log        | 5.0   | 315  | 0.0755          | 0.6056    | 0.6565 | 0.6300 | 0.9752   |


### Framework versions

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