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---
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
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