transformers safetensors longformer token-classification generated_from_trainer base_model:LennartKeller/longformer-gottbert-base-8192-aw512 autotrain_compatible endpoints_compatible region:us
---
base_model: LennartKeller/longformer-gottbert-base-8192-aw512
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: de_longformer_abstr_summ
  results: []
---

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# de_longformer_abstr_summ

This model is a fine-tuned version of [LennartKeller/longformer-gottbert-base-8192-aw512](https://huggingface.co/LennartKeller/longformer-gottbert-base-8192-aw512) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2916
- Precision: 0.2656
- Recall: 0.2673
- F1: 0.2665
- Accuracy: 0.8948

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2741        | 1.0   | 1171 | 0.2860          | 0.0914    | 0.0307 | 0.0459 | 0.8979   |
| 0.2474        | 2.0   | 2342 | 0.2694          | 0.2918    | 0.2508 | 0.2697 | 0.8982   |
| 0.2074        | 3.0   | 3513 | 0.2916          | 0.2656    | 0.2673 | 0.2665 | 0.8948   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2
