---
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
datasets:
- generator
model-index:
- name: stt
  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. -->

# stt

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1619
- Wer Lug: 0.161
- Wer Eng: 0.096
- Wer Mean: 0.129

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Lug | Wer Eng | Wer Mean |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:--------:|
| 0.1876        | 0.1   | 500  | 0.1711          | 0.183   | 0.106   | 0.144    |
| 0.1971        | 0.2   | 1000 | 0.1702          | 0.172   | 0.106   | 0.139    |
| 0.1898        | 0.3   | 1500 | 0.1687          | 0.168   | 0.108   | 0.138    |
| 0.1903        | 0.4   | 2000 | 0.1686          | 0.165   | 0.103   | 0.134    |
| 0.1888        | 0.5   | 2500 | 0.1663          | 0.165   | 0.096   | 0.131    |
| 0.1908        | 1.1   | 3000 | 0.1637          | 0.16    | 0.095   | 0.127    |
| 0.1792        | 1.2   | 3500 | 0.1642          | 0.157   | 0.094   | 0.125    |
| 0.1963        | 1.3   | 4000 | 0.1625          | 0.158   | 0.095   | 0.127    |
| 0.184         | 1.4   | 4500 | 0.1623          | 0.158   | 0.094   | 0.126    |
| 0.1888        | 1.5   | 5000 | 0.1619          | 0.161   | 0.096   | 0.129    |


### Framework versions

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