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# model

This model is a fine-tuned version of [cmarkea/distilcamembert-base](https://huggingface.co/cmarkea/distilcamembert-base) on the allocine dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0254

## 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: 20.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.4388        | 1.0   | 157  | 2.1637          |
| 2.288         | 2.0   | 314  | 2.1697          |
| 2.2444        | 3.0   | 471  | 2.1150          |
| 2.2166        | 4.0   | 628  | 2.0906          |
| 2.1754        | 5.0   | 785  | 2.0899          |
| 2.1604        | 6.0   | 942  | 2.0797          |
| 2.1299        | 7.0   | 1099 | 2.0589          |
| 2.1195        | 8.0   | 1256 | 2.0178          |
| 2.1258        | 9.0   | 1413 | 2.0348          |
| 2.1071        | 10.0  | 1570 | 2.0090          |
| 2.0888        | 11.0  | 1727 | 2.0047          |
| 2.0792        | 12.0  | 1884 | 2.0219          |
| 2.0687        | 13.0  | 2041 | 2.0080          |
| 2.0527        | 14.0  | 2198 | 2.0298          |
| 2.0589        | 15.0  | 2355 | 1.9869          |
| 2.0518        | 16.0  | 2512 | 2.0152          |
| 2.0409        | 17.0  | 2669 | 2.0247          |
| 2.0507        | 18.0  | 2826 | 1.9928          |
| 2.0366        | 19.0  | 2983 | 2.0175          |
| 2.0386        | 20.0  | 3140 | 1.9487          |


### Framework versions

- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

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

model
=====


This model is a fine-tuned version of cmarkea/distilcamembert-base on the allocine dataset.
It achieves the following results on the evaluation set:


* Loss: 2.0254


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: 20.0


### Training results



### Framework versions


* Transformers 4.21.2
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* 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: 20.0 ### Training results ### Framework versions


* Transformers 4.21.2
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #camembert #fill-mask #generated_from_trainer #dataset-allocine #license-mit #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: 20.0 ### Training results ### Framework versions


* Transformers 4.21.2
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #camembert #fill-mask #generated_from_trainer #dataset-allocine #license-mit #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: 20.0### Training results### Framework versions


* Transformers 4.21.2
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1