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

# Yakut-ASR

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: 0.2140
- Wer: 0.2772

## 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: 8
- seed: 42
- optimizer: Use 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 6.0192        | 0.2132 | 100  | 4.4580          | 0.9999 |
| 3.5904        | 0.4264 | 200  | 3.1478          | 1.0    |
| 2.5173        | 0.6397 | 300  | 0.3987          | 0.4625 |
| 0.2948        | 0.8529 | 400  | 0.2442          | 0.3075 |
| 0.2407        | 1.0661 | 500  | 0.2367          | 0.3170 |
| 0.2278        | 1.2793 | 600  | 0.2280          | 0.2914 |
| 0.2279        | 1.4925 | 700  | 0.2341          | 0.2963 |
| 0.2097        | 1.7058 | 800  | 0.2303          | 0.3138 |
| 0.2317        | 1.9190 | 900  | 0.2253          | 0.2889 |
| 0.1898        | 2.1322 | 1000 | 0.2187          | 0.2795 |
| 0.1925        | 2.3454 | 1100 | 0.2262          | 0.2951 |
| 0.211         | 2.5586 | 1200 | 0.2205          | 0.2909 |
| 0.1942        | 2.7719 | 1300 | 0.2192          | 0.2792 |
| 0.169         | 2.9851 | 1400 | 0.2213          | 0.2835 |
| 0.178         | 3.1983 | 1500 | 0.2148          | 0.2795 |
| 0.1862        | 3.4115 | 1600 | 0.2145          | 0.2803 |
| 0.1896        | 3.6247 | 1700 | 0.2154          | 0.2788 |
| 0.1813        | 3.8380 | 1800 | 0.2140          | 0.2772 |


### Framework versions

- Transformers 4.49.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0