---
library_name: transformers
language:
- hy
license: cc-by-4.0
base_model: facebook/mms-1b-all
tags:
- automatic-speech-recognition
- Chillarmo/common_voice_20_armenian
- mms
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-common_voice_20-hy-mms-finetune
  results: []
datasets:
- Chillarmo/common_voice_20_armenian
pipeline_tag: automatic-speech-recognition
---

# wav2vec2-common_voice_20-hy-mms-finetune

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the COMMON_VOICE_20_ARMENIAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1588
- Wer: 0.2465

## 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: 32
- 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: 4.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| No log        | 0.2137 | 100  | 0.2269          | 0.3076 |
| No log        | 0.4274 | 200  | 0.1915          | 0.2824 |
| No log        | 0.6410 | 300  | 0.1993          | 0.2964 |
| No log        | 0.8547 | 400  | 0.1832          | 0.2735 |
| 0.9965        | 1.0684 | 500  | 0.1764          | 0.2649 |
| 0.9965        | 1.2821 | 600  | 0.1733          | 0.2625 |
| 0.9965        | 1.4957 | 700  | 0.1725          | 0.2592 |
| 0.9965        | 1.7094 | 800  | 0.1706          | 0.2581 |
| 0.9965        | 1.9231 | 900  | 0.1681          | 0.2585 |
| 0.2922        | 2.1368 | 1000 | 0.1694          | 0.2591 |
| 0.2922        | 2.3504 | 1100 | 0.1701          | 0.2575 |
| 0.2922        | 2.5641 | 1200 | 0.1701          | 0.2614 |
| 0.2922        | 2.7778 | 1300 | 0.1654          | 0.2535 |
| 0.2922        | 2.9915 | 1400 | 0.1644          | 0.2517 |
| 0.2788        | 3.2051 | 1500 | 0.1636          | 0.2540 |
| 0.2788        | 3.4188 | 1600 | 0.1616          | 0.2512 |
| 0.2788        | 3.6325 | 1700 | 0.1600          | 0.2470 |
| 0.2788        | 3.8462 | 1800 | 0.1587          | 0.2464 |


### Framework versions

- Transformers 4.51.0
- Pytorch 2.2.1+cu121
- Datasets 3.5.0
- Tokenizers 0.21.1