--- base_model: vinai/phobert-base tags: - generated_from_trainer metrics: - accuracy model-index: - name: checkpoint results: [] --- # checkpoint This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.1674 - Accuracy: 0.4286 ## 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: 4 - eval_batch_size: 4 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.01 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 7 | 1.3602 | 0.5714 | | No log | 2.0 | 14 | 1.3269 | 0.5714 | | No log | 3.0 | 21 | 1.2438 | 0.2857 | | No log | 4.0 | 28 | 1.1971 | 0.4286 | | No log | 5.0 | 35 | 1.2036 | 0.2857 | | No log | 6.0 | 42 | 1.1996 | 0.2857 | | No log | 7.0 | 49 | 1.1651 | 0.4286 | | No log | 8.0 | 56 | 1.1406 | 0.4286 | | No log | 9.0 | 63 | 1.1620 | 0.4286 | | No log | 10.0 | 70 | 1.1674 | 0.4286 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.0 - Datasets 2.1.0 - Tokenizers 0.13.3