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# jplu-wikiann

This model is a fine-tuned version of [jplu/tf-camembert-base](https://huggingface.co/jplu/tf-camembert-base) on the wikiann dataset.
It achieves the following results on the evaluation set:
- precision: 0.8980
- recall: 0.9097
- f1: 0.9038
- accuracy: 0.9464

## 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:
- num_train_epochs: 5
- train_batch_size: 16
- eval_batch_size: 32
- learning_rate: 2e-05
- weight_decay_rate: 0.01
- num_warmup_steps: 0
- fp16: True

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.0
- Tokenizers 0.10.3

{"language": ["fr"], "datasets": ["wikiann"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "jplu-wikiann", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "wikiann", "type": "wikiann", "args": "default"}, "metrics": [{"type": "precision", "value": 0.897994120055078, "name": "precision"}, {"type": "recall", "value": 0.9097421203438395, "name": "recall"}, {"type": "f1", "value": 0.9038299466242158, "name": "f1"}, {"type": "accuracy", "value": 0.9464171271196716, "name": "accuracy"}]}]}]}
fr dataset:wikiann model-index region:us
TAGS
#fr #dataset-wikiann #model-index #region-us 




# jplu-wikiann

This model is a fine-tuned version of jplu/tf-camembert-base on the wikiann dataset.
It achieves the following results on the evaluation set:
- precision: 0.8980
- recall: 0.9097
- f1: 0.9038
- accuracy: 0.9464

## 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:
- num_train_epochs: 5
- train_batch_size: 16
- eval_batch_size: 32
- learning_rate: 2e-05
- weight_decay_rate: 0.01
- num_warmup_steps: 0
- fp16: True

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.0
- Tokenizers 0.10.3

# jplu-wikiann

This model is a fine-tuned version of jplu/tf-camembert-base on the wikiann dataset.
It achieves the following results on the evaluation set:
- precision: 0.8980
- recall: 0.9097
- f1: 0.9038
- accuracy: 0.9464 ## 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:
- num_train_epochs: 5
- train_batch_size: 16
- eval_batch_size: 32
- learning_rate: 2e-05
- weight_decay_rate: 0.01
- num_warmup_steps: 0
- fp16: True ### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.0
- Tokenizers 0.10.3
TAGS
#fr #dataset-wikiann #model-index #region-us 
 # jplu-wikiann

This model is a fine-tuned version of jplu/tf-camembert-base on the wikiann dataset.
It achieves the following results on the evaluation set:
- precision: 0.8980
- recall: 0.9097
- f1: 0.9038
- accuracy: 0.9464 ## 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:
- num_train_epochs: 5
- train_batch_size: 16
- eval_batch_size: 32
- learning_rate: 2e-05
- weight_decay_rate: 0.01
- num_warmup_steps: 0
- fp16: True ### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.0
- Tokenizers 0.10.3
passage: TAGS
#fr #dataset-wikiann #model-index #region-us 
# jplu-wikiann

This model is a fine-tuned version of jplu/tf-camembert-base on the wikiann dataset.
It achieves the following results on the evaluation set:
- precision: 0.8980
- recall: 0.9097
- f1: 0.9038
- accuracy: 0.9464## 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:
- num_train_epochs: 5
- train_batch_size: 16
- eval_batch_size: 32
- learning_rate: 2e-05
- weight_decay_rate: 0.01
- num_warmup_steps: 0
- fp16: True### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.0
- Tokenizers 0.10.3