
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# twitter-roberta-base-sentiment-latest-finetuned-FG-CONCAT_SENTENCE-H-NEWS

This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.6335
- Accuracy: 0.5275
- F1: 0.5198

## 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: 6e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 61   | 1.0568          | 0.4396   | 0.2684 |
| No log        | 2.0   | 122  | 1.0518          | 0.4396   | 0.2684 |
| No log        | 3.0   | 183  | 1.0584          | 0.4396   | 0.2684 |
| No log        | 4.0   | 244  | 1.1720          | 0.3956   | 0.3223 |
| No log        | 5.0   | 305  | 1.2473          | 0.5275   | 0.5196 |
| No log        | 6.0   | 366  | 1.0789          | 0.5220   | 0.5301 |
| No log        | 7.0   | 427  | 1.3556          | 0.5604   | 0.5426 |
| No log        | 8.0   | 488  | 1.7314          | 0.5330   | 0.5158 |
| 0.8045        | 9.0   | 549  | 2.2774          | 0.5330   | 0.5161 |
| 0.8045        | 10.0  | 610  | 2.8362          | 0.4451   | 0.4512 |
| 0.8045        | 11.0  | 671  | 2.9130          | 0.5275   | 0.4931 |
| 0.8045        | 12.0  | 732  | 3.1023          | 0.5110   | 0.5010 |
| 0.8045        | 13.0  | 793  | 3.2670          | 0.5385   | 0.5208 |
| 0.8045        | 14.0  | 854  | 3.4151          | 0.4945   | 0.4856 |
| 0.8045        | 15.0  | 915  | 3.7614          | 0.4615   | 0.4458 |
| 0.8045        | 16.0  | 976  | 3.5224          | 0.5220   | 0.5122 |
| 0.0535        | 17.0  | 1037 | 3.5196          | 0.5165   | 0.5102 |
| 0.0535        | 18.0  | 1098 | 3.5791          | 0.5110   | 0.5039 |
| 0.0535        | 19.0  | 1159 | 3.6220          | 0.5220   | 0.5137 |
| 0.0535        | 20.0  | 1220 | 3.6335          | 0.5275   | 0.5198 |


### Framework versions

- Transformers 4.16.2
- Pytorch 1.9.1
- Datasets 1.18.4
- Tokenizers 0.11.6

{"tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "twitter-roberta-base-sentiment-latest-finetuned-FG-CONCAT_SENTENCE-H-NEWS", "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-sentiment-latest-finetuned-FG-CONCAT\_SENTENCE-H-NEWS
==========================================================================


This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-sentiment-latest on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 3.6335
* Accuracy: 0.5275
* F1: 0.5198


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: 6e-05
* train\_batch\_size: 12
* eval\_batch\_size: 12
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20


### Training results



### Framework versions


* Transformers 4.16.2
* Pytorch 1.9.1
* Datasets 1.18.4
* Tokenizers 0.11.6



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 6e-05
* train\_batch\_size: 12
* eval\_batch\_size: 12
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.16.2
* Pytorch 1.9.1
* Datasets 1.18.4
* Tokenizers 0.11.6
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: 6e-05
* train\_batch\_size: 12
* eval\_batch\_size: 12
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.16.2
* Pytorch 1.9.1
* Datasets 1.18.4
* Tokenizers 0.11.6
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: 6e-05
* train\_batch\_size: 12
* eval\_batch\_size: 12
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20### Training results### Framework versions


* Transformers 4.16.2
* Pytorch 1.9.1
* Datasets 1.18.4
* Tokenizers 0.11.6