---
license: mit
base_model: microsoft/MiniLM-L12-H384-uncased
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- f1
model-index:
- name: minisss
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: emotion
      type: emotion
      config: split
      split: validation
      args: split
    metrics:
    - name: F1
      type: f1
      value: 0.9361370380020481
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# minisss

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: 0.1791
- F1: 0.9361

## 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: 5e-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 | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.1818        | 1.0   | 250  | 0.8298          | 0.5948 |
| 0.6392        | 2.0   | 500  | 0.3998          | 0.9005 |
| 0.3246        | 3.0   | 750  | 0.2472          | 0.9301 |
| 0.2151        | 4.0   | 1000 | 0.1937          | 0.9341 |
| 0.1707        | 5.0   | 1250 | 0.1791          | 0.9361 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2