---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: mms_kik
  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. -->

# mms_kik

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: inf
- Wer: 0.1756

## 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: 0.001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- 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
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 4.4384        | 0.1576 | 100  | inf             | 0.4287 |
| 0.5264        | 0.3152 | 200  | inf             | 0.3938 |
| 0.4716        | 0.4728 | 300  | inf             | 0.3655 |
| 0.4084        | 0.6304 | 400  | inf             | 0.3319 |
| 0.3953        | 0.7880 | 500  | inf             | 0.3340 |
| 0.3605        | 0.9456 | 600  | inf             | 0.3109 |
| 0.3601        | 1.1032 | 700  | inf             | 0.2919 |
| 0.3368        | 1.2608 | 800  | inf             | 0.2746 |
| 0.3102        | 1.4184 | 900  | inf             | 0.2691 |
| 0.3209        | 1.5760 | 1000 | inf             | 0.2602 |
| 0.2975        | 1.7336 | 1100 | inf             | 0.2488 |
| 0.2741        | 1.8913 | 1200 | inf             | 0.2356 |
| 0.271         | 2.0489 | 1300 | inf             | 0.2297 |
| 0.2494        | 2.2065 | 1400 | inf             | 0.2233 |
| 0.254         | 2.3641 | 1500 | inf             | 0.2110 |
| 0.2484        | 2.5217 | 1600 | inf             | 0.2117 |
| 0.2416        | 2.6793 | 1700 | inf             | 0.2020 |
| 0.2366        | 2.8369 | 1800 | inf             | 0.1985 |
| 0.2313        | 2.9945 | 1900 | inf             | 0.1959 |
| 0.2228        | 3.1521 | 2000 | inf             | 0.1897 |
| 0.2138        | 3.3097 | 2100 | inf             | 0.1868 |
| 0.2116        | 3.4673 | 2200 | inf             | 0.1822 |
| 0.223         | 3.6249 | 2300 | inf             | 0.1788 |
| 0.2144        | 3.7825 | 2400 | inf             | 0.1774 |
| 0.2131        | 3.9401 | 2500 | inf             | 0.1756 |


### Framework versions

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