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# camembert-base-finetuned-paraphrase

This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on the pawsx dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2708
- Accuracy: 0.9085
- F1: 0.9089

## 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:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.3918        | 1.0   | 772  | 0.3211          | 0.869    | 0.8696 |
| 0.2103        | 2.0   | 1544 | 0.2448          | 0.9075   | 0.9077 |
| 0.1622        | 3.0   | 2316 | 0.2577          | 0.9055   | 0.9059 |
| 0.1344        | 4.0   | 3088 | 0.2708          | 0.9085   | 0.9089 |


### Framework versions

- Transformers 4.19.3
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["pawsx"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "camembert-base-finetuned-paraphrase", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "pawsx", "type": "pawsx", "args": "fr"}, "metrics": [{"type": "accuracy", "value": 0.9085, "name": "Accuracy"}, {"type": "f1", "value": 0.9088724090678741, "name": "F1"}]}]}]}
transformers pytorch tensorboard camembert text-classification generated_from_trainer dataset:pawsx license:mit model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #camembert #text-classification #generated_from_trainer #dataset-pawsx #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 

camembert-base-finetuned-paraphrase
===================================


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


* Loss: 0.2708
* Accuracy: 0.9085
* F1: 0.9089


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:


* learning\_rate: 2e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4


### Training results



### Framework versions


* Transformers 4.19.3
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4 ### Training results ### Framework versions


* Transformers 4.19.3
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #camembert #text-classification #generated_from_trainer #dataset-pawsx #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4 ### Training results ### Framework versions


* Transformers 4.19.3
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #camembert #text-classification #generated_from_trainer #dataset-pawsx #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4### Training results### Framework versions


* Transformers 4.19.3
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1