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# twitter_RoBERTa_base_sentence_itr0_1e-05_all_01_03_2022-13_53_11

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: 0.4118
- Accuracy: 0.8446
- F1: 0.8968
- Precision: 0.8740
- Recall: 0.9207

## 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 | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 390  | 0.3532          | 0.8451   | 0.8990 | 0.8997    | 0.8983 |
| 0.4111        | 2.0   | 780  | 0.3381          | 0.8561   | 0.9080 | 0.8913    | 0.9253 |
| 0.3031        | 3.0   | 1170 | 0.3490          | 0.8537   | 0.9034 | 0.9152    | 0.8919 |
| 0.2408        | 4.0   | 1560 | 0.3562          | 0.8671   | 0.9148 | 0.9       | 0.9300 |
| 0.2408        | 5.0   | 1950 | 0.3725          | 0.8659   | 0.9131 | 0.9074    | 0.9189 |


### Framework versions

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

{"tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1", "precision", "recall"], "model-index": [{"name": "twitter_RoBERTa_base_sentence_itr0_1e-05_all_01_03_2022-13_53_11", "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 

twitter\_RoBERTa\_base\_sentence\_itr0\_1e-05\_all\_01\_03\_2022-13\_53\_11
===========================================================================


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: 0.4118
* Accuracy: 0.8446
* F1: 0.8968
* Precision: 0.8740
* Recall: 0.9207


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