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# minilm-fintuned-emotion

This model is a fine-tuned version of [microsoft/MiniLM-L12-H384-uncased](https://huggingface.co/microsoft/MiniLM-L12-H384-uncased) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3814

## 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: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 250  | 1.0790          |
| No log        | 2.0   | 500  | 0.6965          |
| No log        | 3.0   | 750  | 0.4934          |
| No log        | 4.0   | 1000 | 0.4077          |
| No log        | 5.0   | 1250 | 0.3814          |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["emotion"], "base_model": "microsoft/MiniLM-L12-H384-uncased", "model-index": [{"name": "minilm-fintuned-emotion", "results": []}]}
transformers tensorboard safetensors bert text-classification generated_from_trainer dataset:emotion base_model:microsoft/MiniLM-L12-H384-uncased license:mit autotrain_compatible endpoints_compatible region:us