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# tmp9770t4k0

This model is a fine-tuned version of [nlptown/bert-base-multilingual-uncased-sentiment](https://huggingface.co/nlptown/bert-base-multilingual-uncased-sentiment) on an [muchocine](https://huggingface.co/datasets/muchocine) dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.6629
- Train Accuracy: 0.7345
- Validation Loss: 1.4827
- Validation Accuracy: 0.5
- Epoch: 2

## 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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 1305, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 1.3718     | 0.3908         | 1.2647          | 0.4381              | 0     |
| 1.0808     | 0.5330         | 1.2672          | 0.4742              | 1     |
| 0.6629     | 0.7345         | 1.4827          | 0.5                 | 2     |


### Framework versions

- Transformers 4.17.0
- TensorFlow 2.8.0
- Datasets 1.18.4
- Tokenizers 0.11.6

{"license": "mit", "tags": ["generated_from_keras_callback"], "base_model": "nlptown/bert-base-multilingual-uncased-sentiment", "model-index": [{"name": "tmp9770t4k0", "results": []}]}
transformers tf bert text-classification generated_from_keras_callback base_model:nlptown/bert-base-multilingual-uncased-sentiment license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #bert #text-classification #generated_from_keras_callback #base_model-nlptown/bert-base-multilingual-uncased-sentiment #license-mit #autotrain_compatible #endpoints_compatible #region-us 

tmp9770t4k0
===========


This model is a fine-tuned version of nlptown/bert-base-multilingual-uncased-sentiment on an muchocine dataset.
It achieves the following results on the evaluation set:


* Train Loss: 0.6629
* Train Accuracy: 0.7345
* Validation Loss: 1.4827
* Validation Accuracy: 0.5
* Epoch: 2


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': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 5e-05, 'decay\_steps': 1305, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.17.0
* TensorFlow 2.8.0
* Datasets 1.18.4
* Tokenizers 0.11.6



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'learning\_rate': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 5e-05, 'decay\_steps': 1305, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.17.0
* TensorFlow 2.8.0
* Datasets 1.18.4
* Tokenizers 0.11.6
TAGS
#transformers #tf #bert #text-classification #generated_from_keras_callback #base_model-nlptown/bert-base-multilingual-uncased-sentiment #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'learning\_rate': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 5e-05, 'decay\_steps': 1305, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.17.0
* TensorFlow 2.8.0
* Datasets 1.18.4
* Tokenizers 0.11.6
passage: TAGS
#transformers #tf #bert #text-classification #generated_from_keras_callback #base_model-nlptown/bert-base-multilingual-uncased-sentiment #license-mit #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'learning\_rate': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 5e-05, 'decay\_steps': 1305, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32### Training results### Framework versions


* Transformers 4.17.0
* TensorFlow 2.8.0
* Datasets 1.18.4
* Tokenizers 0.11.6