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---
library_name: transformers
license: apache-2.0
base_model: allenai/longformer-base-4096
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9265
- Accuracy: 0.881
- Precision: 0.8604
- Recall: 0.9788
- F1: 0.9158

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.3194        | 1.0   | 157  | 0.4800          | 0.81     | 0.7827    | 0.9864 | 0.8728 |
| 0.2475        | 2.0   | 314  | 0.3097          | 0.88     | 0.8670    | 0.9667 | 0.9142 |
| 0.1697        | 3.0   | 471  | 0.5044          | 0.859    | 0.8291    | 0.9909 | 0.9028 |
| 0.0833        | 4.0   | 628  | 0.3149          | 0.911    | 0.9243    | 0.9425 | 0.9333 |
| 0.0582        | 5.0   | 785  | 0.5629          | 0.885    | 0.8709    | 0.9697 | 0.9177 |
| 0.029         | 6.0   | 942  | 0.7728          | 0.873    | 0.8541    | 0.9743 | 0.9102 |
| 0.0186        | 7.0   | 1099 | 1.0292          | 0.865    | 0.8355    | 0.9909 | 0.9066 |
| 0.0007        | 8.0   | 1256 | 0.9823          | 0.875    | 0.8508    | 0.9834 | 0.9123 |
| 0.0211        | 9.0   | 1413 | 0.8580          | 0.89     | 0.8708    | 0.9788 | 0.9217 |
| 0.0086        | 10.0  | 1570 | 0.9265          | 0.881    | 0.8604    | 0.9788 | 0.9158 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1