---
license: mit
base_model: numind/NuNER-v1.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: nuner-v1_fewnerd_coarse_super
  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_fewnerd_coarse_super

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: 0.1433
- Precision: 0.7813
- Recall: 0.8145
- F1: 0.7976
- Accuracy: 0.9547

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 16
- 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1498        | 1.0   | 2059 | 0.1477          | 0.7710    | 0.8013 | 0.7859 | 0.9522   |
| 0.1368        | 2.0   | 4118 | 0.1422          | 0.7797    | 0.8101 | 0.7946 | 0.9540   |
| 0.1139        | 3.0   | 6177 | 0.1433          | 0.7813    | 0.8145 | 0.7976 | 0.9547   |


### Framework versions

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