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# twitter-roberta-base-sentiment-latest-finetuned-FG-SINGLE_SENTENCE-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: 3.2822
- Accuracy: 0.6305
- F1: 0.6250

## 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: 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 321  | 0.9646          | 0.5624   | 0.4048 |
| 0.9537        | 2.0   | 642  | 0.9474          | 0.5644   | 0.4176 |
| 0.9537        | 3.0   | 963  | 0.9008          | 0.5903   | 0.5240 |
| 0.858         | 4.0   | 1284 | 0.9939          | 0.5999   | 0.5846 |
| 0.5908        | 5.0   | 1605 | 1.0947          | 0.6108   | 0.6026 |
| 0.5908        | 6.0   | 1926 | 1.2507          | 0.5740   | 0.5823 |
| 0.3676        | 7.0   | 2247 | 1.4717          | 0.6128   | 0.6017 |
| 0.2246        | 8.0   | 2568 | 1.6726          | 0.5965   | 0.6003 |
| 0.2246        | 9.0   | 2889 | 1.8041          | 0.6380   | 0.6298 |
| 0.1468        | 10.0  | 3210 | 1.9796          | 0.6053   | 0.6026 |
| 0.1161        | 11.0  | 3531 | 2.0988          | 0.6237   | 0.6202 |
| 0.1161        | 12.0  | 3852 | 2.4171          | 0.5944   | 0.5989 |
| 0.0916        | 13.0  | 4173 | 2.3326          | 0.6374   | 0.6288 |
| 0.0916        | 14.0  | 4494 | 2.5472          | 0.6360   | 0.6245 |
| 0.0661        | 15.0  | 4815 | 2.9127          | 0.6176   | 0.6187 |
| 0.0454        | 16.0  | 5136 | 2.9133          | 0.6326   | 0.6276 |
| 0.0454        | 17.0  | 5457 | 3.1299          | 0.6210   | 0.6162 |
| 0.0337        | 18.0  | 5778 | 3.1828          | 0.6224   | 0.6188 |
| 0.0223        | 19.0  | 6099 | 3.2655          | 0.6299   | 0.6223 |
| 0.0223        | 20.0  | 6420 | 3.2822          | 0.6305   | 0.6250 |


### 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-SINGLE_SENTENCE-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-SINGLE\_SENTENCE-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: 3.2822
* Accuracy: 0.6305
* F1: 0.6250


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: 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: 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: 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: 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: 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: 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: 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: 20### Training results### Framework versions


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