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

# longformer_result_detection

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: 0.1156
- Precision: 0.6277
- Recall: 0.6694
- F1: 0.6479
- Accuracy: 0.9802

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 348  | 0.0716          | 0.4966    | 0.6050 | 0.5455 | 0.9740   |
| 0.1189        | 2.0   | 696  | 0.0634          | 0.5302    | 0.6195 | 0.5714 | 0.9770   |
| 0.0588        | 3.0   | 1044 | 0.0760          | 0.5518    | 0.6424 | 0.5937 | 0.9774   |
| 0.0588        | 4.0   | 1392 | 0.0760          | 0.6121    | 0.6528 | 0.6318 | 0.9785   |
| 0.0282        | 5.0   | 1740 | 0.0910          | 0.6107    | 0.6424 | 0.6261 | 0.9792   |
| 0.0167        | 6.0   | 2088 | 0.1372          | 0.6       | 0.5364 | 0.5664 | 0.9745   |
| 0.0167        | 7.0   | 2436 | 0.1144          | 0.6028    | 0.6216 | 0.6121 | 0.9793   |
| 0.0087        | 8.0   | 2784 | 0.1011          | 0.6120    | 0.6590 | 0.6346 | 0.9805   |
| 0.0061        | 9.0   | 3132 | 0.1239          | 0.6315    | 0.6341 | 0.6328 | 0.9802   |
| 0.0061        | 10.0  | 3480 | 0.1156          | 0.6277    | 0.6694 | 0.6479 | 0.9802   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1