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---
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
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