---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: Longformer_v5
  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_v5

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: 0.7919
- Precision: 0.8516
- Recall: 0.8678
- F1: 0.6520
- Accuracy: 0.8259

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.7744        | 1.0   | 1012 | 0.5785          | 0.8375    | 0.8501 | 0.5798 | 0.8098   |
| 0.5211        | 2.0   | 2024 | 0.5415          | 0.8434    | 0.8801 | 0.6251 | 0.8282   |
| 0.3996        | 3.0   | 3036 | 0.5565          | 0.8500    | 0.8766 | 0.6303 | 0.8274   |
| 0.2964        | 4.0   | 4048 | 0.6017          | 0.8617    | 0.8546 | 0.6415 | 0.8240   |
| 0.2187        | 5.0   | 5060 | 0.6660          | 0.8485    | 0.8718 | 0.6431 | 0.8271   |
| 0.1603        | 6.0   | 6072 | 0.7235          | 0.8493    | 0.8759 | 0.6544 | 0.8290   |
| 0.1208        | 7.0   | 7084 | 0.7919          | 0.8516    | 0.8678 | 0.6520 | 0.8259   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1