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# maxime7770/model

This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.1211
- Validation Loss: 0.4812
- Epoch: 49

## 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': 2e-05, 'decay_steps': 650, '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-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 1.5966     | 1.5898          | 0     |
| 1.5577     | 1.5576          | 1     |
| 1.5034     | 1.4761          | 2     |
| 1.4034     | 1.3538          | 3     |
| 1.2864     | 1.2163          | 4     |
| 1.1502     | 1.0980          | 5     |
| 1.0085     | 0.9988          | 6     |
| 0.8828     | 0.9130          | 7     |
| 0.7863     | 0.8445          | 8     |
| 0.7036     | 0.7871          | 9     |
| 0.6322     | 0.7399          | 10    |
| 0.5731     | 0.7030          | 11    |
| 0.5180     | 0.6714          | 12    |
| 0.4757     | 0.6432          | 13    |
| 0.4366     | 0.6204          | 14    |
| 0.4057     | 0.6006          | 15    |
| 0.3743     | 0.5827          | 16    |
| 0.3475     | 0.5689          | 17    |
| 0.3221     | 0.5577          | 18    |
| 0.2971     | 0.5467          | 19    |
| 0.2815     | 0.5372          | 20    |
| 0.2700     | 0.5297          | 21    |
| 0.2521     | 0.5225          | 22    |
| 0.2343     | 0.5168          | 23    |
| 0.2265     | 0.5117          | 24    |
| 0.2143     | 0.5074          | 25    |
| 0.2063     | 0.5038          | 26    |
| 0.1941     | 0.5001          | 27    |
| 0.1843     | 0.4976          | 28    |
| 0.1782     | 0.4949          | 29    |
| 0.2012     | 0.4938          | 30    |
| 0.1691     | 0.4930          | 31    |
| 0.1626     | 0.4910          | 32    |
| 0.1884     | 0.4886          | 33    |
| 0.1547     | 0.4870          | 34    |
| 0.1492     | 0.4858          | 35    |
| 0.1445     | 0.4850          | 36    |
| 0.1415     | 0.4842          | 37    |
| 0.1383     | 0.4836          | 38    |
| 0.1374     | 0.4832          | 39    |
| 0.1336     | 0.4826          | 40    |
| 0.1322     | 0.4823          | 41    |
| 0.1295     | 0.4820          | 42    |
| 0.1268     | 0.4818          | 43    |
| 0.1261     | 0.4816          | 44    |
| 0.1253     | 0.4815          | 45    |
| 0.1275     | 0.4814          | 46    |
| 0.1247     | 0.4812          | 47    |
| 0.1256     | 0.4812          | 48    |
| 0.1211     | 0.4812          | 49    |


### Framework versions

- Transformers 4.18.0
- TensorFlow 2.8.0
- Datasets 2.1.0
- Tokenizers 0.12.1

{"license": "mit", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "maxime7770/model", "results": []}]}
transformers tf camembert text-classification generated_from_keras_callback license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #camembert #text-classification #generated_from_keras_callback #license-mit #autotrain_compatible #endpoints_compatible #region-us 

maxime7770/model
================


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


* Train Loss: 0.1211
* Validation Loss: 0.4812
* Epoch: 49


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': 2e-05, 'decay\_steps': 650, '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-08, 'amsgrad': False}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.18.0
* TensorFlow 2.8.0
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'learning\_rate': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 2e-05, 'decay\_steps': 650, '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-08, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.18.0
* TensorFlow 2.8.0
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #tf #camembert #text-classification #generated_from_keras_callback #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': 2e-05, 'decay\_steps': 650, '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-08, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.18.0
* TensorFlow 2.8.0
* Datasets 2.1.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #tf #camembert #text-classification #generated_from_keras_callback #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': 2e-05, 'decay\_steps': 650, '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-08, 'amsgrad': False}
* training\_precision: float32### Training results### Framework versions


* Transformers 4.18.0
* TensorFlow 2.8.0
* Datasets 2.1.0
* Tokenizers 0.12.1