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# pretrained_model

This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the go_emotions dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0568
- F1: 0.5868
- Roc Auc: 0.7616
- Accuracy: 0.4821

## 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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.1205        | 1.0   | 679  | 0.0865          | 0.5632 | 0.7347  | 0.4458   |
| 0.0859        | 2.0   | 1358 | 0.0829          | 0.5717 | 0.7378  | 0.4521   |
| 0.0727        | 3.0   | 2037 | 0.0827          | 0.5897 | 0.7523  | 0.4753   |
| 0.0629        | 4.0   | 2716 | 0.0857          | 0.5808 | 0.7535  | 0.4652   |
| 0.0568        | 5.0   | 3395 | 0.0904          | 0.5868 | 0.7616  | 0.4821   |
| 0.0423        | 6.0   | 4074 | 0.0989          | 0.5806 | 0.7682  | 0.4724   |
| 0.0344        | 7.0   | 4753 | 0.1079          | 0.5736 | 0.7657  | 0.4650   |
| 0.0296        | 8.0   | 5432 | 0.1158          | 0.5637 | 0.7649  | 0.4504   |
| 0.0206        | 9.0   | 6111 | 0.1200          | 0.5674 | 0.7689  | 0.4486   |
| 0.0177        | 10.0  | 6790 | 0.1240          | 0.5728 | 0.7737  | 0.4547   |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["go_emotions"], "metrics": ["f1", "accuracy"], "model-index": [{"name": "pretrained_model", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "go_emotions", "type": "go_emotions", "config": "simplified", "split": "validation", "args": "simplified"}, "metrics": [{"type": "f1", "value": 0.586801681970308, "name": "F1"}, {"type": "accuracy", "value": 0.4821231109472908, "name": "Accuracy"}]}]}]}
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 

pretrained\_model
=================


This model is a fine-tuned version of roberta-large on the go\_emotions dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0568
* F1: 0.5868
* Roc Auc: 0.7616
* Accuracy: 0.4821


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: 5e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
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: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
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: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10### Training results### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2