---
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: []
---

<!-- 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. -->

# 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: 0.5746
- Precision: 0.1612
- Recall: 0.2474
- F1: 0.1952
- Accuracy: 0.7800

## 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
- 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
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 0.98  | 48   | 0.5548          | 0.0       | 0.0    | 0.0    | 0.7540   |
| No log        | 1.99  | 97   | 0.5185          | 0.1067    | 0.1548 | 0.1263 | 0.7864   |
| No log        | 2.99  | 146  | 0.5068          | 0.0876    | 0.1534 | 0.1115 | 0.7806   |
| No log        | 4.0   | 195  | 0.5145          | 0.2797    | 0.3889 | 0.3254 | 0.7926   |
| No log        | 4.98  | 243  | 0.5097          | 0.2068    | 0.3439 | 0.2583 | 0.7916   |
| No log        | 5.99  | 292  | 0.5073          | 0.1637    | 0.2831 | 0.2075 | 0.7920   |
| No log        | 6.99  | 341  | 0.5316          | 0.1723    | 0.2553 | 0.2058 | 0.7865   |
| No log        | 8.0   | 390  | 0.5480          | 0.1483    | 0.2275 | 0.1795 | 0.7837   |
| No log        | 8.98  | 438  | 0.5587          | 0.1649    | 0.2725 | 0.2055 | 0.7823   |
| No log        | 9.85  | 480  | 0.5746          | 0.1612    | 0.2474 | 0.1952 | 0.7800   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.2.1
- Datasets 2.16.1
- Tokenizers 0.15.0