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---
license: mit
base_model: ayshi/basic_roberta
tags:
- generated_from_keras_callback
model-index:
- name: ayshi/basic_roberta
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. -->
# ayshi/basic_roberta
This model is a fine-tuned version of [ayshi/basic_roberta](https://huggingface.co/ayshi/basic_roberta) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0085
- Validation Loss: 1.0970
- Train Accuracy: 0.8267
- Epoch: 20
## 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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 960, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_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 |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.1061 | 0.9567 | 0.7778 | 0 |
| 0.0565 | 1.0825 | 0.7778 | 1 |
| 0.0362 | 1.0696 | 0.7822 | 2 |
| 0.0396 | 1.0904 | 0.7956 | 3 |
| 0.0308 | 1.0044 | 0.8044 | 4 |
| 0.0748 | 1.0578 | 0.8133 | 5 |
| 0.0392 | 0.9964 | 0.8222 | 6 |
| 0.0166 | 1.0293 | 0.8089 | 7 |
| 0.0174 | 0.9895 | 0.8178 | 8 |
| 0.0114 | 1.0403 | 0.8267 | 9 |
| 0.0141 | 1.0086 | 0.8178 | 10 |
| 0.0145 | 1.0403 | 0.8089 | 11 |
| 0.0194 | 1.3127 | 0.7822 | 12 |
| 0.0134 | 1.2929 | 0.7911 | 13 |
| 0.0377 | 0.8565 | 0.8133 | 14 |
| 0.0251 | 0.9806 | 0.8222 | 15 |
| 0.0130 | 1.0757 | 0.8356 | 16 |
| 0.0100 | 1.1304 | 0.8 | 17 |
| 0.0103 | 1.0859 | 0.8133 | 18 |
| 0.0078 | 1.1050 | 0.8311 | 19 |
| 0.0085 | 1.0970 | 0.8267 | 20 |
### Framework versions
- Transformers 4.34.0
- TensorFlow 2.13.0
- Datasets 2.14.5
- Tokenizers 0.14.1
|