---
license: mit
base_model: numind/NuNER-v1.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: nuner-v1_orgs
  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. -->

# nuner-v1_orgs

This model is a fine-tuned version of [numind/NuNER-v1.0](https://huggingface.co/numind/NuNER-v1.0) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0631
- Precision: 0.7912
- Recall: 0.8045
- F1: 0.7978
- Accuracy: 0.9790

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0631        | 1.0   | 1710 | 0.0566          | 0.7635    | 0.7952 | 0.7790 | 0.9778   |
| 0.0572        | 2.0   | 3420 | 0.0580          | 0.7816    | 0.7925 | 0.7870 | 0.9785   |
| 0.0429        | 3.0   | 5130 | 0.0562          | 0.7869    | 0.8084 | 0.7975 | 0.9790   |
| 0.0336        | 4.0   | 6840 | 0.0631          | 0.7912    | 0.8045 | 0.7978 | 0.9790   |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.0.0+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2