---
license: mit
base_model: numind/NuNER-v2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: nuner-v2_fewnerd_fine_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-v2_fewnerd_fine_super

This model is a fine-tuned version of [numind/NuNER-v2.0](https://huggingface.co/numind/NuNER-v2.0) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2392
- Precision: 0.6818
- Recall: 0.7148
- F1: 0.6979
- Accuracy: 0.9309

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2608        | 1.0   | 2059 | 0.2497          | 0.6512    | 0.7000 | 0.6747 | 0.9255   |
| 0.2153        | 2.0   | 4118 | 0.2364          | 0.6796    | 0.7015 | 0.6904 | 0.9302   |
| 0.1949        | 3.0   | 6177 | 0.2347          | 0.6785    | 0.7110 | 0.6944 | 0.9309   |
| 0.1669        | 4.0   | 8236 | 0.2392          | 0.6818    | 0.7148 | 0.6979 | 0.9309   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2