---
license: apache-2.0
base_model: allenai/longformer-base-4096
tags:
- generated_from_trainer
metrics:
- recall
- precision
model-index:
- name: longformer-8bitadam-2048-main
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# longformer-8bitadam-2048-main

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: 0.0103
- Recall: 0.9643
- Precision: 0.9643
- F5: 0.9643

## 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: 4
- seed: 42
- gradient_accumulation_steps: 4
- 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: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Recall | Precision | F5     |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|
| 0.0015        | 1.0   | 100  | 0.0197          | 1.0    | 0.9032    | 0.9959 |
| 0.0012        | 2.0   | 200  | 0.0179          | 0.9643 | 0.9643    | 0.9643 |
| 0.0008        | 3.0   | 300  | 0.0103          | 0.9643 | 0.9643    | 0.9643 |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2