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# go_emo_gpt

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the go_emotions dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0964
- F1: 0.6010
- Roc Auc: 0.7659
- Accuracy: 0.4996

## 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: 1e-05
- train_batch_size: 1
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: (13023,)
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step   | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:------:|:-------:|:--------:|
| 0.105         | 1.0   | 43410  | 0.0967          | 0.5795 | 0.7476  | 0.4757   |
| 0.0949        | 2.0   | 86820  | 0.0938          | 0.6012 | 0.7636  | 0.5035   |
| 0.0837        | 3.0   | 130230 | 0.0964          | 0.6010 | 0.7659  | 0.4996   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["go_emotions"], "metrics": ["f1", "accuracy"], "model-index": [{"name": "go_emo_gpt", "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": 0.6009707054948864, "name": "F1"}, {"type": "accuracy", "value": 0.49963140434942865, "name": "Accuracy"}]}]}]}
transformers pytorch tensorboard gpt2 text-classification generated_from_trainer dataset:go_emotions license:mit model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #gpt2 #text-classification #generated_from_trainer #dataset-go_emotions #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

go\_emo\_gpt
============


This model is a fine-tuned version of gpt2 on the go\_emotions dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0964
* F1: 0.6010
* Roc Auc: 0.7659
* Accuracy: 0.4996


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: 1e-05
* train\_batch\_size: 1
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: (13023,)
* num\_epochs: 3


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 1
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: (13023,)
* num\_epochs: 3 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #gpt2 #text-classification #generated_from_trainer #dataset-go_emotions #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 1
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: (13023,)
* num\_epochs: 3 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3