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# ko-sroberta-multitask-finetuned-emotion

This model is a fine-tuned version of [jhgan/ko-sroberta-multitask](https://huggingface.co/jhgan/ko-sroberta-multitask) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2960
- Accuracy: 0.907
- F1: 0.9068

## 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: 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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.0684        | 1.0   | 250  | 0.5018          | 0.8465   | 0.8458 |
| 0.4203        | 2.0   | 500  | 0.2960          | 0.907    | 0.9068 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"tags": ["generated_from_trainer"], "datasets": ["emotion"], "metrics": ["accuracy", "f1"], "base_model": "jhgan/ko-sroberta-multitask", "model-index": [{"name": "ko-sroberta-multitask-finetuned-emotion", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "emotion", "type": "emotion", "config": "split", "split": "validation", "args": "split"}, "metrics": [{"type": "accuracy", "value": 0.907, "name": "Accuracy"}, {"type": "f1", "value": 0.9068379504122163, "name": "F1"}]}]}]}
transformers tensorboard safetensors roberta text-classification generated_from_trainer dataset:emotion base_model:jhgan/ko-sroberta-multitask model-index autotrain_compatible endpoints_compatible region:us