---
license: mit
base_model: microsoft/MiniLM-L12-H384-uncased
tags:
- generated_from_trainer
model-index:
- name: minilm-finetuned-emotion-class-model
  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-class-model

This model is a fine-tuned version of [microsoft/MiniLM-L12-H384-uncased](https://huggingface.co./microsoft/MiniLM-L12-H384-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1026
- F1 Score: 0.6649

## 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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.8502        | 1.0   | 270  | 1.4798          | 0.5071   |
| 1.3541        | 2.0   | 540  | 1.2377          | 0.5836   |
| 1.1809        | 3.0   | 810  | 1.1675          | 0.6202   |
| 1.0891        | 4.0   | 1080 | 1.1081          | 0.6522   |
| 1.0205        | 5.0   | 1350 | 1.0815          | 0.6603   |
| 0.9624        | 6.0   | 1620 | 1.0640          | 0.6645   |
| 0.9185        | 7.0   | 1890 | 1.0572          | 0.6689   |
| 0.8811        | 8.0   | 2160 | 1.0433          | 0.6693   |
| 0.8531        | 9.0   | 2430 | 1.0479          | 0.6746   |
| 0.8208        | 10.0  | 2700 | 1.0536          | 0.6697   |
| 0.8014        | 11.0  | 2970 | 1.0564          | 0.6713   |
| 0.7798        | 12.0  | 3240 | 1.0634          | 0.6716   |
| 0.7568        | 13.0  | 3510 | 1.0744          | 0.6698   |
| 0.7414        | 14.0  | 3780 | 1.0782          | 0.6704   |
| 0.7265        | 15.0  | 4050 | 1.0810          | 0.6694   |
| 0.7128        | 16.0  | 4320 | 1.0885          | 0.6684   |
| 0.7054        | 17.0  | 4590 | 1.0917          | 0.6631   |
| 0.6927        | 18.0  | 4860 | 1.0961          | 0.6678   |
| 0.6848        | 19.0  | 5130 | 1.1005          | 0.6644   |
| 0.6742        | 20.0  | 5400 | 1.1026          | 0.6649   |


### Framework versions

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