---
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: 0.1366
- Precision: 0.6230
- Recall: 0.6881
- F1: 0.6539
- Accuracy: 0.9738

## 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   | 410  | 0.0770          | 0.5744    | 0.6056 | 0.5896 | 0.9720   |
| 0.1137        | 2.0   | 820  | 0.0612          | 0.5608    | 0.6398 | 0.5977 | 0.9723   |
| 0.056         | 3.0   | 1230 | 0.0671          | 0.6374    | 0.6861 | 0.6609 | 0.9753   |
| 0.0347        | 4.0   | 1640 | 0.0854          | 0.6026    | 0.7505 | 0.6685 | 0.9754   |
| 0.0221        | 5.0   | 2050 | 0.1062          | 0.6138    | 0.6781 | 0.6444 | 0.9732   |
| 0.0221        | 6.0   | 2460 | 0.1116          | 0.6181    | 0.7002 | 0.6566 | 0.9750   |
| 0.0119        | 7.0   | 2870 | 0.1143          | 0.6405    | 0.7565 | 0.6937 | 0.9768   |
| 0.007         | 8.0   | 3280 | 0.1303          | 0.6712    | 0.6901 | 0.6806 | 0.9747   |
| 0.0058        | 9.0   | 3690 | 0.1347          | 0.6189    | 0.6861 | 0.6508 | 0.9741   |
| 0.0036        | 10.0  | 4100 | 0.1366          | 0.6230    | 0.6881 | 0.6539 | 0.9738   |


### Framework versions

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