
# Greek Media Longformer

This model is a second-stage pretrained version of [dimitriz/greek-longformer-base-4096](https://huggingface.co/dimitriz/greek-longformer-base-4096) trained on the [dimitriz/greek_media_texts](https://huggingface.co/datasets/dimitriz/greek_media_texts) dataset.
It achieves the following results on the evaluation set:

- Loss: 1.1424
- Accuracy: 0.7574

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 6.0

### Training results

### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.2

## Citing & Authors

The model has been officially released with the article "From Pre-training to Meta-Learning: A journey in Low-Resource-Language Representation Learning".
Dimitrios Zaikis and Ioannis Vlahavas.
In: IEEE Access.

If you use the model, please cite the following:

```bibtex

@ARTICLE{10288436,
    author =  {Zaikis, Dimitrios and Vlahavas, Ioannis},
    journal = {IEEE Access},
    title =   {From Pre-training to Meta-Learning: A journey in Low-Resource-Language Representation Learning},
    year =    {2023},
    volume =  {},
    number =  {},
    pages =   {1-1},
    doi =     {10.1109/ACCESS.2023.3326337}
  }

```

{"language": ["el"], "tags": ["text", "language-modeling"], "metrics": ["accuracy"], "model-index": [{"name": "greek-media-longformer-base-4096-uncased", "results": []}]}
transformers pytorch tf longformer feature-extraction text language-modeling el endpoints_compatible region:us
TAGS
#transformers #pytorch #tf #longformer #feature-extraction #text #language-modeling #el #endpoints_compatible #region-us 


# Greek Media Longformer

This model is a second-stage pretrained version of dimitriz/greek-longformer-base-4096 trained on the dimitriz/greek_media_texts dataset.
It achieves the following results on the evaluation set:

- Loss: 1.1424
- Accuracy: 0.7574

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 6.0

### Training results

### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.2

## Citing & Authors

The model has been officially released with the article "From Pre-training to Meta-Learning: A journey in Low-Resource-Language Representation Learning".
Dimitrios Zaikis and Ioannis Vlahavas.
In: IEEE Access.

If you use the model, please cite the following:



# Greek Media Longformer

This model is a second-stage pretrained version of dimitriz/greek-longformer-base-4096 trained on the dimitriz/greek_media_texts dataset.
It achieves the following results on the evaluation set:

- Loss: 1.1424
- Accuracy: 0.7574 ## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 6.0 ### Training results ### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.2 ## Citing & Authors

The model has been officially released with the article "From Pre-training to Meta-Learning: A journey in Low-Resource-Language Representation Learning".
Dimitrios Zaikis and Ioannis Vlahavas.
In: IEEE Access.

If you use the model, please cite the following:
TAGS
#transformers #pytorch #tf #longformer #feature-extraction #text #language-modeling #el #endpoints_compatible #region-us 
 # Greek Media Longformer

This model is a second-stage pretrained version of dimitriz/greek-longformer-base-4096 trained on the dimitriz/greek_media_texts dataset.
It achieves the following results on the evaluation set:

- Loss: 1.1424
- Accuracy: 0.7574 ## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 6.0 ### Training results ### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.2 ## Citing & Authors

The model has been officially released with the article "From Pre-training to Meta-Learning: A journey in Low-Resource-Language Representation Learning".
Dimitrios Zaikis and Ioannis Vlahavas.
In: IEEE Access.

If you use the model, please cite the following:
TAGS
#transformers #pytorch #tf #longformer #feature-extraction #text #language-modeling #el #endpoints_compatible #region-us 
# Greek Media Longformer

This model is a second-stage pretrained version of dimitriz/greek-longformer-base-4096 trained on the dimitriz/greek_media_texts dataset.
It achieves the following results on the evaluation set:

- Loss: 1.1424
- Accuracy: 0.7574## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 6.0### Training results### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.2## Citing & Authors

The model has been officially released with the article "From Pre-training to Meta-Learning: A journey in Low-Resource-Language Representation Learning".
Dimitrios Zaikis and Ioannis Vlahavas.
In: IEEE Access.

If you use the model, please cite the following: