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

# Kabardian-ASR-kaggle

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1748
- Wer: 0.3268

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.6132        | 0.3040 | 200  | 0.4195          | 0.6846 |
| 0.4931        | 0.6079 | 400  | 0.3299          | 0.5413 |
| 0.3934        | 0.9119 | 600  | 0.2873          | 0.5070 |
| 0.3771        | 1.2158 | 800  | 0.2497          | 0.4569 |
| 0.3445        | 1.5198 | 1000 | 0.2516          | 0.4304 |
| 0.3724        | 1.8237 | 1200 | 0.2439          | 0.4079 |
| 0.3265        | 2.1277 | 1400 | 0.2083          | 0.4065 |
| 0.2983        | 2.4316 | 1600 | 0.2082          | 0.3693 |
| 0.3222        | 2.7356 | 1800 | 0.2073          | 0.3688 |
| 0.3461        | 3.0395 | 2000 | 0.1854          | 0.3438 |
| 0.2745        | 3.3435 | 2200 | 0.1813          | 0.3329 |
| 0.2867        | 3.6474 | 2400 | 0.1784          | 0.3258 |
| 0.2715        | 3.9514 | 2600 | 0.1748          | 0.3268 |


### Framework versions

- Transformers 4.49.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.3.0
- Tokenizers 0.21.0