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

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: 0.1084
- Accuracy: 0.964
- Precision: 0.961
- Recall: 0.936
- F1: 0.946

## 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: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1    |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:-----:|
| No log        | 1.0   | 89   | 0.2301          | 0.926    | 0.933     | 0.861  | 0.883 |
| No log        | 2.0   | 178  | 0.1487          | 0.964    | 0.968     | 0.915  | 0.937 |
| No log        | 3.0   | 267  | 0.1084          | 0.964    | 0.961     | 0.936  | 0.946 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.0
- Tokenizers 0.13.3