metadata
license: mit
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: bert-finetuned-Location
results: []
bert-finetuned-Location
This model is a fine-tuned version of dbmdz/bert-base-french-europeana-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5462
- F1: 0.8167
- Roc Auc: 0.8624
- Accuracy: 0.8133
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
---|---|---|---|---|---|---|
0.4229 | 1.0 | 742 | 0.3615 | 0.7402 | 0.8014 | 0.6900 |
0.3722 | 2.0 | 1484 | 0.3103 | 0.7906 | 0.8416 | 0.7796 |
0.262 | 3.0 | 2226 | 0.3364 | 0.8135 | 0.8600 | 0.8100 |
0.2239 | 4.0 | 2968 | 0.4593 | 0.8085 | 0.8561 | 0.8066 |
0.1461 | 5.0 | 3710 | 0.5534 | 0.7923 | 0.8440 | 0.7904 |
0.1333 | 6.0 | 4452 | 0.5462 | 0.8167 | 0.8624 | 0.8133 |
0.0667 | 7.0 | 5194 | 0.6298 | 0.7972 | 0.8479 | 0.7958 |
0.0616 | 8.0 | 5936 | 0.6362 | 0.8075 | 0.8556 | 0.8059 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1