flaubert_base_cased-finetuned-DOP6
This model is a fine-tuned version of flaubert/flaubert_base_cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4109
- Accuracy: 0.8591
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: 4
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.9735 | 1.0 | 110 | 0.6360 | 0.7955 |
0.6305 | 2.0 | 220 | 0.4801 | 0.8227 |
0.4992 | 3.0 | 330 | 0.4163 | 0.8545 |
0.4172 | 4.0 | 440 | 0.4109 | 0.8591 |
Framework versions
- Transformers 4.22.2
- Pytorch 1.12.1+cu113
- Datasets 2.5.2
- Tokenizers 0.12.1
- Downloads last month
- 14
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.