metadata
language:
- fr
datasets:
- wikiann
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: jplu-wikiann
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: wikiann
type: wikiann
args: default
metrics:
- name: precision
type: precision
value: 0.897994120055078
- name: recall
type: recall
value: 0.9097421203438395
- name: f1
type: f1
value: 0.9038299466242158
- name: accuracy
type: accuracy
value: 0.9464171271196716
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