---
license: mit
base_model: microsoft/MiniLM-L12-H384-uncased
tags:
- generated_from_trainer
datasets:
- emotion
model-index:
- name: minilm-fintuned-emotion
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# 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: 0.3649

## 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 250  | 0.2190          |
| No log        | 2.0   | 500  | 0.2935          |
| No log        | 3.0   | 750  | 0.2978          |
| No log        | 4.0   | 1000 | 0.2842          |
| No log        | 5.0   | 1250 | 0.3042          |
| No log        | 6.0   | 1500 | 0.3383          |
| No log        | 7.0   | 1750 | 0.3491          |
| No log        | 8.0   | 2000 | 0.3548          |
| No log        | 9.0   | 2250 | 0.3648          |
| No log        | 10.0  | 2500 | 0.3649          |


### Framework versions

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