---
library_name: transformers
license: mit
base_model: microsoft/MiniLM-L12-H384-uncased
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: minilm-finetuned-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-finetuned-emotion

This model is a fine-tuned version of [microsoft/MiniLM-L12-H384-uncased](https://huggingface.co/microsoft/MiniLM-L12-H384-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4249
- F1: 0.9065

## 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 | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.422         | 1.0   | 250  | 1.0999          | 0.5547 |
| 0.9267        | 2.0   | 500  | 0.7411          | 0.8058 |
| 0.6629        | 3.0   | 750  | 0.5482          | 0.8749 |
| 0.5111        | 4.0   | 1000 | 0.4645          | 0.8970 |
| 0.4399        | 5.0   | 1250 | 0.4249          | 0.9065 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1