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---
license: mit
tags:
- generated_from_keras_callback
model-index:
- name: luiscunhacsc/masked-lm-tpu
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. -->
# luiscunhacsc/masked-lm-tpu
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 9.8209
- Train Accuracy: 0.0113
- Validation Loss: 9.6999
- Validation Accuracy: 0.0188
- 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': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 0.0001, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0001, 'decay_steps': 22325, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 1175, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.001}
- training_precision: float32
### Training results
| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 10.2855 | 0.0000 | 10.2842 | 0.0 | 0 |
| 10.2729 | 0.0000 | 10.2651 | 0.0000 | 1 |
| 10.2599 | 0.0 | 10.2357 | 0.0000 | 2 |
| 10.2335 | 0.0 | 10.1943 | 0.0000 | 3 |
| 10.1915 | 0.0000 | 10.1447 | 0.0000 | 4 |
| 10.1449 | 0.0000 | 10.0705 | 0.0000 | 5 |
| 10.0750 | 0.0000 | 9.9926 | 0.0001 | 6 |
| 10.0099 | 0.0002 | 9.9074 | 0.0023 | 7 |
| 9.9197 | 0.0025 | 9.7964 | 0.0146 | 8 |
| 9.8209 | 0.0113 | 9.6999 | 0.0188 | 9 |
### Framework versions
- Transformers 4.29.2
- TensorFlow 2.12.0
- Tokenizers 0.13.3
|