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# TimShieh/bert-base-cased-finetuned-semeval2017-MLM-tf

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 1.3086
- Validation Loss: 2.3846
- Epoch: 98

## 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: {'inner_optimizer': {'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 3500, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
- training_precision: mixed_float16

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 2.8433     | 2.6662          | 0     |
| 2.7598     | 2.5861          | 1     |
| 2.7534     | 2.5040          | 2     |
| 2.7240     | 2.4523          | 3     |
| 2.6318     | 2.5183          | 4     |
| 2.5957     | 2.4422          | 5     |
| 2.5625     | 2.4058          | 6     |
| 2.5154     | 2.3935          | 7     |
| 2.4640     | 2.3379          | 8     |
| 2.4819     | 2.3405          | 9     |
| 2.4415     | 2.3790          | 10    |
| 2.3893     | 2.3233          | 11    |
| 2.3388     | 2.3790          | 12    |
| 2.3699     | 2.3036          | 13    |
| 2.2846     | 2.2498          | 14    |
| 2.3063     | 2.2773          | 15    |
| 2.2476     | 2.2761          | 16    |
| 2.1773     | 2.2033          | 17    |
| 2.2143     | 2.2317          | 18    |
| 2.2070     | 2.2894          | 19    |
| 2.1538     | 2.2133          | 20    |
| 2.0956     | 2.3578          | 21    |
| 2.1071     | 2.2503          | 22    |
| 2.0790     | 2.3071          | 23    |
| 2.0288     | 2.3034          | 24    |
| 2.0533     | 2.3170          | 25    |
| 2.0120     | 2.2095          | 26    |
| 1.9467     | 2.2245          | 27    |
| 1.9542     | 2.2078          | 28    |
| 1.9432     | 2.3161          | 29    |
| 1.9461     | 2.3124          | 30    |
| 1.9065     | 2.2365          | 31    |
| 1.8745     | 2.1271          | 32    |
| 1.8496     | 2.3026          | 33    |
| 1.8842     | 2.3762          | 34    |
| 1.8175     | 2.2070          | 35    |
| 1.8243     | 2.2866          | 36    |
| 1.7952     | 2.2107          | 37    |
| 1.7777     | 2.3179          | 38    |
| 1.7657     | 2.2338          | 39    |
| 1.7292     | 2.2267          | 40    |
| 1.7378     | 2.2141          | 41    |
| 1.6489     | 2.2372          | 42    |
| 1.6734     | 2.2508          | 43    |
| 1.6657     | 2.2625          | 44    |
| 1.6595     | 2.3270          | 45    |
| 1.6092     | 2.2561          | 46    |
| 1.5995     | 2.1516          | 47    |
| 1.6329     | 2.3223          | 48    |
| 1.6295     | 2.3140          | 49    |
| 1.5856     | 2.2300          | 50    |
| 1.6024     | 2.2130          | 51    |
| 1.5409     | 2.1686          | 52    |
| 1.5413     | 2.2330          | 53    |
| 1.5623     | 2.3331          | 54    |
| 1.5061     | 2.2902          | 55    |
| 1.5053     | 2.3790          | 56    |
| 1.5196     | 2.2583          | 57    |
| 1.4747     | 2.2444          | 58    |
| 1.5104     | 2.3633          | 59    |
| 1.4382     | 2.3433          | 60    |
| 1.4945     | 2.2789          | 61    |
| 1.4732     | 2.2114          | 62    |
| 1.4642     | 2.2824          | 63    |
| 1.4017     | 2.3451          | 64    |
| 1.4142     | 2.2902          | 65    |
| 1.3868     | 2.3788          | 66    |
| 1.4233     | 2.2854          | 67    |
| 1.4314     | 2.4351          | 68    |
| 1.3653     | 2.2845          | 69    |
| 1.4202     | 2.2994          | 70    |
| 1.3817     | 2.2924          | 71    |
| 1.3771     | 2.3026          | 72    |
| 1.3795     | 2.2778          | 73    |
| 1.3843     | 2.3807          | 74    |
| 1.3457     | 2.3068          | 75    |
| 1.3408     | 2.3956          | 76    |
| 1.3737     | 2.2845          | 77    |
| 1.3277     | 2.3673          | 78    |
| 1.3330     | 2.3530          | 79    |
| 1.2938     | 2.2045          | 80    |
| 1.3352     | 2.3202          | 81    |
| 1.3095     | 2.3502          | 82    |
| 1.2982     | 2.2561          | 83    |
| 1.3452     | 2.2632          | 84    |
| 1.2995     | 2.3359          | 85    |
| 1.3235     | 2.2482          | 86    |
| 1.3153     | 2.3753          | 87    |
| 1.3092     | 2.3334          | 88    |
| 1.3178     | 2.4354          | 89    |
| 1.3300     | 2.3763          | 90    |
| 1.3079     | 2.3011          | 91    |
| 1.2800     | 2.3430          | 92    |
| 1.3166     | 2.2550          | 93    |
| 1.2893     | 2.3375          | 94    |
| 1.2898     | 2.3382          | 95    |
| 1.3280     | 2.4488          | 96    |
| 1.3429     | 2.3147          | 97    |
| 1.3086     | 2.3846          | 98    |


### Framework versions

- Transformers 4.26.1
- TensorFlow 2.11.0
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "TimShieh/bert-base-cased-finetuned-semeval2017-MLM-tf", "results": []}]}
transformers tf bert fill-mask generated_from_keras_callback license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #bert #fill-mask #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

TimShieh/bert-base-cased-finetuned-semeval2017-MLM-tf
=====================================================


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


* Train Loss: 1.3086
* Validation Loss: 2.3846
* Epoch: 98


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: {'inner\_optimizer': {'class\_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning\_rate': {'class\_name': 'WarmUp', 'config': {'initial\_learning\_rate': 2e-05, 'decay\_schedule\_fn': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 2e-05, 'decay\_steps': 3500, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '**passive\_serialization**': True}, 'warmup\_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight\_decay\_rate': 0.01}}, 'dynamic': True, 'initial\_scale': 32768.0, 'dynamic\_growth\_steps': 2000}
* training\_precision: mixed\_float16


### Training results



### Framework versions


* Transformers 4.26.1
* TensorFlow 2.11.0
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'inner\_optimizer': {'class\_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning\_rate': {'class\_name': 'WarmUp', 'config': {'initial\_learning\_rate': 2e-05, 'decay\_schedule\_fn': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 2e-05, 'decay\_steps': 3500, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '**passive\_serialization**': True}, 'warmup\_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight\_decay\_rate': 0.01}}, 'dynamic': True, 'initial\_scale': 32768.0, 'dynamic\_growth\_steps': 2000}
* training\_precision: mixed\_float16 ### Training results ### Framework versions


* Transformers 4.26.1
* TensorFlow 2.11.0
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #tf #bert #fill-mask #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'inner\_optimizer': {'class\_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning\_rate': {'class\_name': 'WarmUp', 'config': {'initial\_learning\_rate': 2e-05, 'decay\_schedule\_fn': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 2e-05, 'decay\_steps': 3500, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '**passive\_serialization**': True}, 'warmup\_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight\_decay\_rate': 0.01}}, 'dynamic': True, 'initial\_scale': 32768.0, 'dynamic\_growth\_steps': 2000}
* training\_precision: mixed\_float16 ### Training results ### Framework versions


* Transformers 4.26.1
* TensorFlow 2.11.0
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #tf #bert #fill-mask #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'inner\_optimizer': {'class\_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning\_rate': {'class\_name': 'WarmUp', 'config': {'initial\_learning\_rate': 2e-05, 'decay\_schedule\_fn': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 2e-05, 'decay\_steps': 3500, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '**passive\_serialization**': True}, 'warmup\_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight\_decay\_rate': 0.01}}, 'dynamic': True, 'initial\_scale': 32768.0, 'dynamic\_growth\_steps': 2000}
* training\_precision: mixed\_float16### Training results### Framework versions


* Transformers 4.26.1
* TensorFlow 2.11.0
* Datasets 2.10.1
* Tokenizers 0.13.2