| | --- |
| | license: mit |
| | base_model: xlm-roberta-base |
| | tags: |
| | - generated_from_keras_callback |
| | model-index: |
| | - name: khadija69/roberta_ASE_kgl |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information Keras had access to. You should |
| | probably proofread and complete it, then remove this comment. --> |
| |
|
| | # khadija69/roberta_ASE_kgl |
| |
|
| | This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Train Loss: 0.1987 |
| | - Validation Loss: 0.3653 |
| | - Epoch: 9 |
| |
|
| | ## 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: |
| | - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 1000, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01} |
| | - training_precision: float32 |
| | |
| | ### Training results |
| | |
| | | Train Loss | Validation Loss | Epoch | |
| | |:----------:|:---------------:|:-----:| |
| | | 0.4777 | 0.3498 | 0 | |
| | | 0.3292 | 0.3403 | 1 | |
| | | 0.3056 | 0.3305 | 2 | |
| | | 0.2796 | 0.3372 | 3 | |
| | | 0.2624 | 0.3323 | 4 | |
| | | 0.2468 | 0.3416 | 5 | |
| | | 0.2277 | 0.3364 | 6 | |
| | | 0.2141 | 0.3557 | 7 | |
| | | 0.2057 | 0.3576 | 8 | |
| | | 0.1987 | 0.3653 | 9 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.39.3 |
| | - TensorFlow 2.15.0 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.15.2 |
| | |
