---
license: mit
base_model: numind/NuNER-v1.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: nuner-v1_ontonotes5
  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_ontonotes5

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: 0.0728
- Precision: 0.8712
- Recall: 0.9000
- F1: 0.8853
- Accuracy: 0.9811

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0781        | 1.0   | 936  | 0.0754          | 0.8392    | 0.8843 | 0.8612 | 0.9778   |
| 0.049         | 2.0   | 1873 | 0.0685          | 0.8597    | 0.8935 | 0.8763 | 0.9794   |
| 0.0357        | 3.0   | 2809 | 0.0714          | 0.8608    | 0.9016 | 0.8807 | 0.9806   |
| 0.027         | 4.0   | 3744 | 0.0728          | 0.8712    | 0.9000 | 0.8853 | 0.9811   |


### Framework versions

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