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# ellis-v1-emotion-positive-emotions2

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5876
- Accuracy: 0.8003

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.7042        | 1.0   | 3885  | 0.6515          | 0.7716   |
| 0.6124        | 2.0   | 7770  | 0.5955          | 0.7846   |
| 0.5292        | 3.0   | 11655 | 0.6043          | 0.7944   |
| 0.4543        | 4.0   | 15540 | 0.5876          | 0.8003   |
| 0.3953        | 5.0   | 19425 | 0.6153          | 0.8103   |
| 0.3301        | 6.0   | 23310 | 0.6478          | 0.8100   |
| 0.2737        | 7.0   | 27195 | 0.6919          | 0.8103   |
| 0.2034        | 8.0   | 31080 | 0.7899          | 0.8142   |
| 0.1968        | 9.0   | 34965 | 0.8648          | 0.8151   |
| 0.167         | 10.0  | 38850 | 0.9208          | 0.8154   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.1.0+cu121
- Datasets 2.13.0
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "roberta-base", "model-index": [{"name": "ellis-v1-emotion-positive-emotions2", "results": []}]}
transformers pytorch roberta text-classification generated_from_trainer base_model:roberta-base license:mit autotrain_compatible endpoints_compatible region:us