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# ru_propaganda_opposition_model_without_foreign_agent_mask_large_6

RANLP_2023_ru_propaganda_opposition_model

This model is a fine-tuned version of [DeepPavlov/bert-base-bg-cs-pl-ru-cased](https://huggingface.co/DeepPavlov/bert-base-bg-cs-pl-ru-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0003
- Validation Loss: 0.2103
- Train Accuracy: 0.9606
- Epoch: 14

## 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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 6150, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, '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 |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.2650     | 0.1440          | 0.9452         | 0     |
| 0.0881     | 0.1171          | 0.9529         | 1     |
| 0.0377     | 0.1506          | 0.9573         | 2     |
| 0.0202     | 0.1724          | 0.9562         | 3     |
| 0.0116     | 0.1534          | 0.9617         | 4     |
| 0.0064     | 0.2133          | 0.9540         | 5     |
| 0.0093     | 0.1844          | 0.9628         | 6     |
| 0.0074     | 0.1427          | 0.9606         | 7     |
| 0.0018     | 0.1757          | 0.9639         | 8     |
| 0.0017     | 0.2006          | 0.9606         | 9     |
| 0.0006     | 0.1996          | 0.9595         | 10    |
| 0.0007     | 0.2004          | 0.9628         | 11    |
| 0.0004     | 0.2052          | 0.9628         | 12    |
| 0.0003     | 0.2090          | 0.9606         | 13    |
| 0.0003     | 0.2103          | 0.9606         | 14    |


### Framework versions

- Transformers 4.28.1
- TensorFlow 2.12.0
- Datasets 2.11.0
- Tokenizers 0.13.3

{"tags": ["generated_from_keras_callback"], "model-index": [{"name": "ru_propaganda_opposition_model_without_foreign_agent_mask_large_6", "results": []}]}
transformers tf bert text-classification generated_from_keras_callback autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #bert #text-classification #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #region-us 

ru\_propaganda\_opposition\_model\_without\_foreign\_agent\_mask\_large\_6
==========================================================================


RANLP\_2023\_ru\_propaganda\_opposition\_model


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


* Train Loss: 0.0003
* Validation Loss: 0.2103
* Train Accuracy: 0.9606
* Epoch: 14


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': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 2e-05, 'decay\_steps': 6150, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.28.1
* TensorFlow 2.12.0
* Datasets 2.11.0
* Tokenizers 0.13.3



### 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': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 2e-05, 'decay\_steps': 6150, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.28.1
* TensorFlow 2.12.0
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #tf #bert #text-classification #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #region-us 
 ### 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': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 2e-05, 'decay\_steps': 6150, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.28.1
* TensorFlow 2.12.0
* Datasets 2.11.0
* Tokenizers 0.13.3