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# constituency-brackets-20

This model is a fine-tuned version of [allegro/herbert-base-cased](https://huggingface.co/allegro/herbert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.2020
- Train Acc: 0.9356
- Validation Loss: 0.2929
- Validation Acc: 0.9120
- Epoch: 19

## 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', 'learning_rate': 5e-06, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Train Acc | Validation Loss | Validation Acc | Epoch |
|:----------:|:---------:|:---------------:|:--------------:|:-----:|
| 2.4703     | 0.3783    | 1.4719          | 0.5858         | 0     |
| 1.2149     | 0.6600    | 0.8922          | 0.7269         | 1     |
| 0.8721     | 0.7343    | 0.6914          | 0.7779         | 2     |
| 0.7186     | 0.7715    | 0.6028          | 0.8037         | 3     |
| 0.6239     | 0.7987    | 0.5427          | 0.8240         | 4     |
| 0.5432     | 0.8342    | 0.4469          | 0.8677         | 5     |
| 0.4521     | 0.8665    | 0.4092          | 0.8760         | 6     |
| 0.4100     | 0.8761    | 0.3867          | 0.8819         | 7     |
| 0.3792     | 0.8855    | 0.3761          | 0.8849         | 8     |
| 0.3526     | 0.8926    | 0.3469          | 0.8938         | 9     |
| 0.3304     | 0.8981    | 0.3433          | 0.8944         | 10    |
| 0.3091     | 0.9049    | 0.3329          | 0.8977         | 11    |
| 0.2935     | 0.9081    | 0.3178          | 0.9028         | 12    |
| 0.2769     | 0.9138    | 0.3140          | 0.9032         | 13    |
| 0.2614     | 0.9173    | 0.2994          | 0.9114         | 14    |
| 0.2472     | 0.9213    | 0.2954          | 0.9128         | 15    |
| 0.2344     | 0.9260    | 0.2899          | 0.9142         | 16    |
| 0.2229     | 0.9292    | 0.2971          | 0.9092         | 17    |
| 0.2136     | 0.9322    | 0.2872          | 0.9143         | 18    |
| 0.2020     | 0.9356    | 0.2929          | 0.9120         | 19    |


### Framework versions

- Transformers 4.26.0
- TensorFlow 2.9.2
- Datasets 2.8.0
- Tokenizers 0.13.2

{"license": "cc-by-4.0", "tags": ["generated_from_keras_callback"], "base_model": "allegro/herbert-base-cased", "model-index": [{"name": "constituency-brackets-20", "results": []}]}
transformers tf bert token-classification generated_from_keras_callback base_model:allegro/herbert-base-cased license:cc-by-4.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #bert #token-classification #generated_from_keras_callback #base_model-allegro/herbert-base-cased #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us 

constituency-brackets-20
========================


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


* Train Loss: 0.2020
* Train Acc: 0.9356
* Validation Loss: 0.2929
* Validation Acc: 0.9120
* Epoch: 19


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', 'learning\_rate': 5e-06, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.26.0
* TensorFlow 2.9.2
* Datasets 2.8.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'learning\_rate': 5e-06, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.26.0
* TensorFlow 2.9.2
* Datasets 2.8.0
* Tokenizers 0.13.2
TAGS
#transformers #tf #bert #token-classification #generated_from_keras_callback #base_model-allegro/herbert-base-cased #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'learning\_rate': 5e-06, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.26.0
* TensorFlow 2.9.2
* Datasets 2.8.0
* Tokenizers 0.13.2
TAGS
#transformers #tf #bert #token-classification #generated_from_keras_callback #base_model-allegro/herbert-base-cased #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'learning\_rate': 5e-06, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32### Training results### Framework versions


* Transformers 4.26.0
* TensorFlow 2.9.2
* Datasets 2.8.0
* Tokenizers 0.13.2