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# distilbert-finetuned-go-emotion

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on go_emotion dataset.
It achieves the following results on the train set:
- Loss: 0.111
- Accuracy Thresh: 0.962

## Evalution Output:

 'eval_accuracy_thresh': 0.9619810581207275,
 'eval_loss': 0.11105917394161224



### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy Thresh |
|:-------------:|:-----:|:----:|:---------------:|:---------------:|
| 0.1264        | 1.0   | 1357 | 0.1133          | 0.9618          |
| 0.1102        | 2.0   | 2714 | 0.1115          | 0.9620          |
| 0.1057        | 3.0   | 4071 | 0.1110          | 0.9619          |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
{"language": ["en"], "license": "apache-2.0", "tags": ["text-classification", "go-emotion", "pytorch"], "datasets": ["go_emotions"], "metrics": ["accuracy"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "distilbert-finetuned-go-emotion", "results": []}]}
transformers safetensors distilbert text-classification go-emotion pytorch en dataset:go_emotions base_model:distilbert-base-uncased license:apache-2.0 endpoints_compatible region:us