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# test-german-t5-prompted-germanquad

eval_loss = 0.5907255411148071  
eval_rouge1 = 62.0922  
eval_rouge2 = 47.2761  
eval_rougeL = 61.7706  
eval_rougeLsum = 61.8036  
eval_runtime = 4501.8065  
eval_samples_per_second = 5.487  
eval_steps_per_second = 2.743  



## 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: 5.6e-05
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Framework versions

- Transformers 4.16.0.dev0
- Pytorch 1.9.1+cu102
- Datasets 1.18.0
- Tokenizers 0.11.0

{"tags": ["generated_from_trainer"], "widget": [{"text": "Philipp ist 26 Jahre alt und lebt in N\u00fcrnberg, Deutschland. Derzeit arbeitet er als Machine Learning Engineer und Tech Lead bei Hugging Face, um k\u00fcnstliche Intelligenz durch Open Source und Open Science zu demokratisieren.\n\nWelches Ziel hat Hugging Face?\n"}], "model-index": [{"name": "test-german-t5-prompted-germanquad", "results": []}]}
transformers pytorch tensorboard safetensors t5 text2text-generation generated_from_trainer autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 




# test-german-t5-prompted-germanquad

eval_loss = 0.5907255411148071  
eval_rouge1 = 62.0922  
eval_rouge2 = 47.2761  
eval_rougeL = 61.7706  
eval_rougeLsum = 61.8036  
eval_runtime = 4501.8065  
eval_samples_per_second = 5.487  
eval_steps_per_second = 2.743  



## 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: 5.6e-05
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Framework versions

- Transformers 4.16.0.dev0
- Pytorch 1.9.1+cu102
- Datasets 1.18.0
- Tokenizers 0.11.0

# test-german-t5-prompted-germanquad

eval_loss = 0.5907255411148071  
eval_rouge1 = 62.0922  
eval_rouge2 = 47.2761  
eval_rougeL = 61.7706  
eval_rougeLsum = 61.8036  
eval_runtime = 4501.8065  
eval_samples_per_second = 5.487  
eval_steps_per_second = 2.743 ## 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: 5.6e-05
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3 ### Framework versions

- Transformers 4.16.0.dev0
- Pytorch 1.9.1+cu102
- Datasets 1.18.0
- Tokenizers 0.11.0
TAGS
#transformers #pytorch #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # test-german-t5-prompted-germanquad

eval_loss = 0.5907255411148071  
eval_rouge1 = 62.0922  
eval_rouge2 = 47.2761  
eval_rougeL = 61.7706  
eval_rougeLsum = 61.8036  
eval_runtime = 4501.8065  
eval_samples_per_second = 5.487  
eval_steps_per_second = 2.743 ## 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: 5.6e-05
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3 ### Framework versions

- Transformers 4.16.0.dev0
- Pytorch 1.9.1+cu102
- Datasets 1.18.0
- Tokenizers 0.11.0
passage: TAGS
#transformers #pytorch #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# test-german-t5-prompted-germanquad

eval_loss = 0.5907255411148071  
eval_rouge1 = 62.0922  
eval_rouge2 = 47.2761  
eval_rougeL = 61.7706  
eval_rougeLsum = 61.8036  
eval_runtime = 4501.8065  
eval_samples_per_second = 5.487  
eval_steps_per_second = 2.743## 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: 5.6e-05
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3### Framework versions

- Transformers 4.16.0.dev0
- Pytorch 1.9.1+cu102
- Datasets 1.18.0
- Tokenizers 0.11.0