metadata
tags:
- generated_from_keras_callback
model-index:
- name: cruiser/twitter_roberta_final_model
results: []
cruiser/twitter_roberta_final_model
This model is a fine-tuned version of cardiffnlp/twitter-xlm-roberta-base-sentiment on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0648
- Validation Loss: 1.0107
- Train Accuracy: 0.7943
- 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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 1e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 34090, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'passive_serialization': True}, 'warmup_steps': 250, 'power': 1.0, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
Training results
| Train Loss | Validation Loss | Train Accuracy | Epoch |
|---|---|---|---|
| 0.5482 | 0.4911 | 0.7991 | 0 |
| 0.4389 | 0.5053 | 0.7972 | 1 |
| 0.3567 | 0.5357 | 0.7935 | 2 |
| 0.2774 | 0.6193 | 0.7872 | 3 |
| 0.2080 | 0.6732 | 0.7989 | 4 |
| 0.1545 | 0.7639 | 0.7889 | 5 |
| 0.1162 | 0.8836 | 0.7855 | 6 |
| 0.0943 | 0.9301 | 0.7903 | 7 |
| 0.0768 | 0.9647 | 0.7929 | 8 |
| 0.0648 | 1.0107 | 0.7943 | 9 |
Framework versions
- Transformers 4.27.4
- TensorFlow 2.11.0
- Datasets 2.1.0
- Tokenizers 0.13.2