transformers tf roberta fill-mask generated_from_keras_callback base_model:roberta-base license:mit autotrain_compatible endpoints_compatible region:us
---
license: mit
base_model: roberta-base
tags:
- generated_from_keras_callback
model-index:
- name: pcmill/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. -->

# pcmill/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: 9.9285
- Train Accuracy: 0.0044
- Validation Loss: 9.8057
- Validation Accuracy: 0.0197
- 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': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 0.0001, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0001, 'decay_steps': 22325, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 1175, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, '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 |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 10.3759    | 0.0000         | 10.3822         | 0.0                 | 0     |
| 10.3601    | 0.0000         | 10.3615         | 0.0                 | 1     |
| 10.3529    | 0.0            | 10.3315         | 0.0000              | 2     |
| 10.3210    | 0.0            | 10.2957         | 0.0000              | 3     |
| 10.2824    | 0.0            | 10.2382         | 0.0                 | 4     |
| 10.2333    | 0.0            | 10.1677         | 0.0                 | 5     |
| 10.1625    | 0.0            | 10.0990         | 0.0                 | 6     |
| 10.1024    | 0.0000         | 10.0062         | 0.0001              | 7     |
| 10.0126    | 0.0004         | 9.9072          | 0.0058              | 8     |
| 9.9285     | 0.0044         | 9.8057          | 0.0197              | 9     |


### Framework versions

- Transformers 4.38.1
- TensorFlow 2.15.0
- Tokenizers 0.15.2
