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# Text Classification GoEmotions

This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the [go_emotions](https://huggingface.co/datasets/go_emotions) dataset.
It achieves the following results on the test set (with a threshold of 0.15):
- Accuracy: 0.4175
- Precision: 0.4934
- Recall: 0.5621
- F1: 0.5102

## Code

Code for training this model can be found [here](https://github.com/tasinhoque/go-emotions-text-classification).

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:

- learning_rate: 5e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Validation Loss | Accuracy | Precision |  Recall  |    F1    |
| :-----------: | :---: | :-------------: | :------: | :-------: | :------: | :------: |
|    No log     |  1.0  |    0.088978     | 0.404349 | 0.480763  | 0.456827 | 0.444685 |
|    0.10620    |  2.0  |    0.082806     | 0.411353 | 0.460896  | 0.536386 | 0.486819 |
|    0.10620    |  3.0  |    0.081338     | 0.420199 | 0.519828  | 0.561297 | 0.522716 |

### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0
- Datasets 2.1.0
- Tokenizers 0.12.1

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["go_emotions"], "metrics": ["f1"], "model-index": [{"name": "roberta-large-goemotions", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "go_emotions", "type": "multilabel_classification", "config": "simplified", "split": "test", "args": "simplified"}, "metrics": [{"type": "f1", "value": 0.5102, "name": "F1"}]}, {"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "go_emotions", "type": "multilabel_classification", "config": "simplified", "split": "validation", "args": "simplified"}, "metrics": [{"type": "f1", "value": 0.5227, "name": "F1"}]}]}]}
transformers pytorch tensorboard roberta text-classification generated_from_trainer dataset:go_emotions license:mit model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #dataset-go_emotions #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 

Text Classification GoEmotions
==============================


This model is a fine-tuned version of roberta-large on the go\_emotions dataset.
It achieves the following results on the test set (with a threshold of 0.15):


* Accuracy: 0.4175
* Precision: 0.4934
* Recall: 0.5621
* F1: 0.5102


Code
----


Code for training this model can be found here.


Training procedure
------------------


### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 128
* eval\_batch\_size: 128
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3


### Training results



### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 128
* eval\_batch\_size: 128
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #dataset-go_emotions #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 128
* eval\_batch\_size: 128
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #dataset-go_emotions #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 128
* eval\_batch\_size: 128
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3### Training results### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.1.0
* Tokenizers 0.12.1