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# benjip/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: 9.8771
- Train Accuracy: 0.0086
- Validation Loss: 9.7741
- Validation Accuracy: 0.0208
- 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 |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 10.3084    | 0.0000         | 10.3098         | 0.0000              | 0     |
| 10.2947    | 0.0            | 10.2947         | 0.0                 | 1     |
| 10.2840    | 0.0000         | 10.2631         | 0.0                 | 2     |
| 10.2555    | 0.0            | 10.2269         | 0.0                 | 3     |
| 10.2161    | 0.0000         | 10.1759         | 0.0000              | 4     |
| 10.1694    | 0.0            | 10.1119         | 0.0                 | 5     |
| 10.1126    | 0.0            | 10.0506         | 0.0000              | 6     |
| 10.0476    | 0.0001         | 9.9642          | 0.0013              | 7     |
| 9.9589     | 0.0015         | 9.8694          | 0.0116              | 8     |
| 9.8771     | 0.0086         | 9.7741          | 0.0208              | 9     |


### Framework versions

- Transformers 4.29.2
- TensorFlow 2.12.0
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "benjip/masked-lm-tpu", "results": []}]}
transformers tf roberta fill-mask generated_from_keras_callback license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #roberta #fill-mask #generated_from_keras_callback #license-mit #autotrain_compatible #endpoints_compatible #region-us 

benjip/masked-lm-tpu
====================


This model is a fine-tuned version of roberta-base on an unknown dataset.
It achieves the following results on the evaluation set:


* Train Loss: 9.8771
* Train Accuracy: 0.0086
* Validation Loss: 9.7741
* Validation Accuracy: 0.0208
* 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



### Framework versions


* Transformers 4.29.2
* TensorFlow 2.12.0
* Tokenizers 0.13.3



### 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 ### Framework versions


* Transformers 4.29.2
* TensorFlow 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #tf #roberta #fill-mask #generated_from_keras_callback #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### 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 ### Framework versions


* Transformers 4.29.2
* TensorFlow 2.12.0
* Tokenizers 0.13.3