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# goemotions_bertspanish_finetunig_f

This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-cased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased) on the go_emotions dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2528
- Accuracy: 0.4433
- F1: 0.3108

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7

### Training results



### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "datasets": ["go_emotions"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "goemotions_bertspanish_finetunig_f", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "go_emotions", "type": "go_emotions", "config": "simplified", "split": "test", "args": "simplified"}, "metrics": [{"type": "accuracy", "value": 0.44333333333333336, "name": "Accuracy"}, {"type": "f1", "value": 0.3107562259034207, "name": "F1"}]}]}]}
transformers pytorch tensorboard bert text-classification generated_from_trainer dataset:go_emotions model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #dataset-go_emotions #model-index #autotrain_compatible #endpoints_compatible #region-us 




# goemotions_bertspanish_finetunig_f

This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on the go_emotions dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2528
- Accuracy: 0.4433
- F1: 0.3108

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7

### Training results



### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

# goemotions_bertspanish_finetunig_f

This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on the go_emotions dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2528
- Accuracy: 0.4433
- F1: 0.3108 ## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7 ### Training results ### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #dataset-go_emotions #model-index #autotrain_compatible #endpoints_compatible #region-us 
 # goemotions_bertspanish_finetunig_f

This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on the go_emotions dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2528
- Accuracy: 0.4433
- F1: 0.3108 ## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7 ### Training results ### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3