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# fr-camembert-base-finetuned

This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3301

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.2487        | 1.0   | 124  | 2.8169          |
| 2.6851        | 2.0   | 248  | 2.6374          |
| 2.6175        | 3.0   | 372  | 2.6431          |
| 2.5366        | 4.0   | 496  | 2.4475          |
| 2.4529        | 5.0   | 620  | 2.4647          |
| 2.4002        | 6.0   | 744  | 2.4846          |
| 2.3914        | 7.0   | 868  | 2.4187          |
| 2.3439        | 8.0   | 992  | 2.4819          |
| 2.2797        | 9.0   | 1116 | 2.3769          |
| 2.3065        | 10.0  | 1240 | 2.4536          |
| 2.2499        | 11.0  | 1364 | 2.4079          |
| 2.2254        | 12.0  | 1488 | 2.3755          |
| 2.218         | 13.0  | 1612 | 2.3189          |
| 2.2059        | 14.0  | 1736 | 2.3628          |
| 2.158         | 15.0  | 1860 | 2.4482          |
| 2.1871        | 16.0  | 1984 | 2.3020          |
| 2.154         | 17.0  | 2108 | 2.3485          |
| 2.1906        | 18.0  | 2232 | 2.4602          |
| 2.1853        | 19.0  | 2356 | 2.2482          |
| 2.1334        | 20.0  | 2480 | 2.3699          |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "fr-camembert-base-finetuned", "results": []}]}
transformers pytorch tensorboard camembert fill-mask generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #camembert #fill-mask #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

fr-camembert-base-finetuned
===========================


This model is a fine-tuned version of camembert-base on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 2.3301


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: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #camembert #fill-mask #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3