| --- |
| tags: |
| - generated_from_keras_callback |
| model-index: |
| - name: cruiser/roberta_tensorflow_test |
| 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. --> |
|
|
| # cruiser/roberta_tensorflow_test |
|
|
| This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Train Loss: 0.1366 |
| - Train Accuracy: 0.9537 |
| - Validation Loss: 0.8098 |
| - Validation Accuracy: 0.7875 |
| - Epoch: 5 |
|
|
| ## 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': 'Adam', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 34350, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False} |
| - training_precision: float32 |
|
|
| ### Training results |
|
|
| | Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch | |
| |:----------:|:--------------:|:---------------:|:-------------------:|:-----:| |
| | 0.6043 | 0.7502 | 0.5449 | 0.7756 | 0 | |
| | 0.4868 | 0.8044 | 0.5104 | 0.7807 | 1 | |
| | 0.3846 | 0.8472 | 0.5949 | 0.7705 | 2 | |
| | 0.2873 | 0.8908 | 0.6515 | 0.7858 | 3 | |
| | 0.1965 | 0.9293 | 0.7051 | 0.7813 | 4 | |
| | 0.1366 | 0.9537 | 0.8098 | 0.7875 | 5 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.20.1 |
| - TensorFlow 2.9.2 |
| - Datasets 2.1.0 |
| - Tokenizers 0.12.1 |
|
|
