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# xlm-roberta-base-amazon-en-es-fr-mlm

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the Yaxin/amazon_reviews_multi dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3936
- Accuracy: 0.6951

## 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: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results



### Framework versions

- Transformers 4.18.0.dev0
- Pytorch 1.11.0
- Datasets 2.0.0
- Tokenizers 0.11.6

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["Yaxin/amazon_reviews_multi"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-amazon-en-es-fr-mlm", "results": [{"task": {"type": "fill-mask", "name": "Masked Language Modeling"}, "dataset": {"name": "Yaxin/amazon_reviews_multi", "type": "Yaxin/amazon_reviews_multi"}, "metrics": [{"type": "accuracy", "value": 0.6951035447140035, "name": "Accuracy"}]}]}]}
transformers pytorch xlm-roberta fill-mask generated_from_trainer dataset:Yaxin/amazon_reviews_multi license:mit model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #xlm-roberta #fill-mask #generated_from_trainer #dataset-Yaxin/amazon_reviews_multi #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 




# xlm-roberta-base-amazon-en-es-fr-mlm

This model is a fine-tuned version of xlm-roberta-base on the Yaxin/amazon_reviews_multi dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3936
- Accuracy: 0.6951

## 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: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results



### Framework versions

- Transformers 4.18.0.dev0
- Pytorch 1.11.0
- Datasets 2.0.0
- Tokenizers 0.11.6

# xlm-roberta-base-amazon-en-es-fr-mlm

This model is a fine-tuned version of xlm-roberta-base on the Yaxin/amazon_reviews_multi dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3936
- Accuracy: 0.6951 ## 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: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0 ### Training results ### Framework versions

- Transformers 4.18.0.dev0
- Pytorch 1.11.0
- Datasets 2.0.0
- Tokenizers 0.11.6
TAGS
#transformers #pytorch #xlm-roberta #fill-mask #generated_from_trainer #dataset-Yaxin/amazon_reviews_multi #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
 # xlm-roberta-base-amazon-en-es-fr-mlm

This model is a fine-tuned version of xlm-roberta-base on the Yaxin/amazon_reviews_multi dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3936
- Accuracy: 0.6951 ## 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: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0 ### Training results ### Framework versions

- Transformers 4.18.0.dev0
- Pytorch 1.11.0
- Datasets 2.0.0
- Tokenizers 0.11.6
TAGS
#transformers #pytorch #xlm-roberta #fill-mask #generated_from_trainer #dataset-Yaxin/amazon_reviews_multi #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
# xlm-roberta-base-amazon-en-es-fr-mlm

This model is a fine-tuned version of xlm-roberta-base on the Yaxin/amazon_reviews_multi dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3936
- Accuracy: 0.6951## 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: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0### Training results### Framework versions

- Transformers 4.18.0.dev0
- Pytorch 1.11.0
- Datasets 2.0.0
- Tokenizers 0.11.6