---
library_name: transformers
license: mit
base_model: cjber/reddit-ner-place_names
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
- wer
model-index:
- name: reddit-ner-place_names-finetuned
  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. -->

# reddit-ner-place_names-finetuned

This model is a fine-tuned version of [cjber/reddit-ner-place_names](https://huggingface.co/cjber/reddit-ner-place_names) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0301
- Precision: 0.8010
- Recall: 0.8406
- F1: 0.8203
- Accuracy: 0.9929
- Wer: 0.0071

## 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 | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:------:|
| 0.024         | 1.0   | 1535 | 0.0214          | 0.7826    | 0.8414 | 0.8109 | 0.9924   | 0.0075 |
| 0.0173        | 2.0   | 3070 | 0.0203          | 0.7865    | 0.8526 | 0.8182 | 0.9928   | 0.0072 |
| 0.0109        | 3.0   | 4605 | 0.0234          | 0.8166    | 0.8351 | 0.8257 | 0.9930   | 0.0070 |
| 0.0078        | 4.0   | 6140 | 0.0264          | 0.8179    | 0.8259 | 0.8219 | 0.9930   | 0.0070 |
| 0.005         | 5.0   | 7675 | 0.0301          | 0.8010    | 0.8406 | 0.8203 | 0.9929   | 0.0071 |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1