---
license: apache-2.0
base_model: allenai/longformer-base-4096
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: longformer-base-4096-ner-invoice
  results: []
---

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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/deepakm-rajendra-irl/huggingface/runs/9vrqo2pl)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/deepakm-rajendra-irl/huggingface/runs/9vrqo2pl)
# longformer-base-4096-ner-invoice

This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co./allenai/longformer-base-4096) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0113
- Precision: 0.9741
- Recall: 0.9847
- F1: 0.9793
- Accuracy: 0.9975

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 138  | 0.0484          | 0.8748    | 0.8996 | 0.8870 | 0.9887   |
| No log        | 2.0   | 276  | 0.0139          | 0.9626    | 0.9769 | 0.9697 | 0.9969   |
| No log        | 3.0   | 414  | 0.0113          | 0.9741    | 0.9847 | 0.9793 | 0.9975   |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1