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# twitter-roberta-base-mar2022-finetuned-emotion

This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-mar2022](https://huggingface.co/cardiffnlp/twitter-roberta-base-mar2022) on the tweet_eval dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5146
- Accuracy: 0.8191
- F1: 0.8171

## 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: 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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.8945        | 1.0   | 102  | 0.5831          | 0.7995   | 0.7887 |
| 0.5176        | 2.0   | 204  | 0.5266          | 0.8235   | 0.8200 |


### Framework versions

- Transformers 4.19.3
- Pytorch 1.11.0+cu102
- Datasets 2.2.2
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "datasets": ["tweet_eval"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "twitter-roberta-base-mar2022-finetuned-emotion", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "tweet_eval", "type": "tweet_eval", "args": "emotion"}, "metrics": [{"type": "accuracy", "value": 0.8191414496833216, "name": "Accuracy"}, {"type": "f1", "value": 0.8170974933422602, "name": "F1"}]}]}]}
transformers pytorch roberta text-classification generated_from_trainer dataset:tweet_eval model-index autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #dataset-tweet_eval #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 

twitter-roberta-base-mar2022-finetuned-emotion
==============================================


This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-mar2022 on the tweet\_eval dataset.
It achieves the following results on the evaluation set:


* Loss: 0.5146
* Accuracy: 0.8191
* F1: 0.8171


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: 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: 2


### Training results



### Framework versions


* Transformers 4.19.3
* Pytorch 1.11.0+cu102
* Datasets 2.2.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: 2 ### Training results ### Framework versions


* Transformers 4.19.3
* Pytorch 1.11.0+cu102
* Datasets 2.2.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #dataset-tweet_eval #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: 2 ### Training results ### Framework versions


* Transformers 4.19.3
* Pytorch 1.11.0+cu102
* Datasets 2.2.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #dataset-tweet_eval #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: 2### Training results### Framework versions


* Transformers 4.19.3
* Pytorch 1.11.0+cu102
* Datasets 2.2.2
* Tokenizers 0.12.1