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# DistilBERTFINAL_ctxSentence_TRAIN_all_TEST_french_second_train_set_NULL_True

This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base](https://huggingface.co/cardiffnlp/twitter-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4024
- Precision: 0.8643
- Recall: 0.9769
- F1: 0.9171
- Accuracy: 0.8594

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 130  | 0.4920          | 0.7766    | 1.0    | 0.8742 | 0.7766   |
| No log        | 2.0   | 260  | 0.4469          | 0.7885    | 1.0    | 0.8818 | 0.7918   |
| No log        | 3.0   | 390  | 0.3860          | 0.8248    | 0.9860 | 0.8982 | 0.8265   |
| 0.462         | 4.0   | 520  | 0.3948          | 0.8441    | 0.9832 | 0.9084 | 0.8460   |
| 0.462         | 5.0   | 650  | 0.3694          | 0.8632    | 0.9693 | 0.9132 | 0.8568   |


### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3

{"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "DistilBERTFINAL_ctxSentence_TRAIN_all_TEST_french_second_train_set_NULL_True", "results": []}]}
transformers pytorch tensorboard roberta text-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

DistilBERTFINAL\_ctxSentence\_TRAIN\_all\_TEST\_french\_second\_train\_set\_NULL\_True
======================================================================================


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


* Loss: 0.4024
* Precision: 0.8643
* Recall: 0.9769
* F1: 0.9171
* Accuracy: 0.8594


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: 1e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5


### Training results



### Framework versions


* Transformers 4.15.0
* Pytorch 1.10.1+cu113
* Datasets 1.18.0
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.15.0
* Pytorch 1.10.1+cu113
* Datasets 1.18.0
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.15.0
* Pytorch 1.10.1+cu113
* Datasets 1.18.0
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5### Training results### Framework versions


* Transformers 4.15.0
* Pytorch 1.10.1+cu113
* Datasets 1.18.0
* Tokenizers 0.10.3