---
tags:
- generated_from_trainer
model-index:
- name: bart_large_teaser_de_v2
  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. -->

# bart_large_teaser_de_v2

This model was trained from scratch on an unknown dataset.

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

{'eval_loss': 0.2028738558292389, 'eval_score': 80.750962016922, 'eval_counts': [342359, 316072, 304925, 294258], 'eval_totals': [376475, 371475, 366475, 361475], 'eval_precisions': [90.93804369480046, 85.08567198330978, 83.20485708438503, 81.40479977868456], 'eval_bp': 0.9490684186878129, 'eval_sys_len': 376475, 'eval_ref_len': 396155, 'eval_runtime': 431.9447, 'eval_samples_per_second': 11.576, 'eval_steps_per_second': 0.363}


## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Framework versions

- Transformers 4.16.2
- Pytorch 1.11.0a0+bfe5ad2
- Datasets 1.18.3
- Tokenizers 0.11.0