---
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-mms-1b-kazakh-speech2ner-ksc_synthetic-4b-10ep
  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. -->

# wav2vec2-large-mms-1b-kazakh-speech2ner-ksc_synthetic-4b-10ep

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: nan
- Wer: 1.0

## 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Wer |
|:-------------:|:-----:|:------:|:---------------:|:---:|
| 0.0           | 0.15  | 8000   | nan             | 1.0 |
| 0.0           | 0.3   | 16000  | nan             | 1.0 |
| 0.0           | 0.44  | 24000  | nan             | 1.0 |
| 0.0           | 0.59  | 32000  | nan             | 1.0 |
| 0.0           | 0.74  | 40000  | nan             | 1.0 |
| 0.0           | 0.89  | 48000  | nan             | 1.0 |
| 0.0           | 1.03  | 56000  | nan             | 1.0 |
| 0.0           | 1.18  | 64000  | nan             | 1.0 |
| 0.0           | 1.33  | 72000  | nan             | 1.0 |
| 0.0           | 1.48  | 80000  | nan             | 1.0 |
| 0.0           | 1.62  | 88000  | nan             | 1.0 |
| 0.0           | 1.77  | 96000  | nan             | 1.0 |
| 0.0           | 1.92  | 104000 | nan             | 1.0 |
| 0.0           | 2.07  | 112000 | nan             | 1.0 |
| 0.0           | 2.21  | 120000 | nan             | 1.0 |
| 0.0           | 2.36  | 128000 | nan             | 1.0 |
| 0.0           | 2.51  | 136000 | nan             | 1.0 |
| 0.0           | 2.66  | 144000 | nan             | 1.0 |
| 0.0           | 2.8   | 152000 | nan             | 1.0 |
| 0.0           | 2.95  | 160000 | nan             | 1.0 |
| 0.0           | 3.1   | 168000 | nan             | 1.0 |
| 0.0           | 3.25  | 176000 | nan             | 1.0 |
| 0.0           | 3.39  | 184000 | nan             | 1.0 |
| 0.0           | 3.54  | 192000 | nan             | 1.0 |
| 0.0           | 3.69  | 200000 | nan             | 1.0 |
| 0.0           | 3.84  | 208000 | nan             | 1.0 |
| 0.0           | 3.98  | 216000 | nan             | 1.0 |
| 0.0           | 4.13  | 224000 | nan             | 1.0 |
| 0.0           | 4.28  | 232000 | nan             | 1.0 |
| 0.0           | 4.43  | 240000 | nan             | 1.0 |
| 0.0           | 4.57  | 248000 | nan             | 1.0 |
| 0.0           | 4.72  | 256000 | nan             | 1.0 |
| 0.0           | 4.87  | 264000 | nan             | 1.0 |
| 0.0           | 5.02  | 272000 | nan             | 1.0 |
| 0.0           | 5.16  | 280000 | nan             | 1.0 |
| 0.0           | 5.31  | 288000 | nan             | 1.0 |
| 0.0           | 5.46  | 296000 | nan             | 1.0 |
| 0.0           | 5.61  | 304000 | nan             | 1.0 |
| 0.0           | 5.75  | 312000 | nan             | 1.0 |
| 0.0           | 5.9   | 320000 | nan             | 1.0 |
| 0.0           | 6.05  | 328000 | nan             | 1.0 |
| 0.0           | 6.2   | 336000 | nan             | 1.0 |
| 0.0           | 6.34  | 344000 | nan             | 1.0 |
| 0.0           | 6.49  | 352000 | nan             | 1.0 |
| 0.0           | 6.64  | 360000 | nan             | 1.0 |
| 0.0           | 6.79  | 368000 | nan             | 1.0 |
| 0.0           | 6.93  | 376000 | nan             | 1.0 |
| 0.0           | 7.08  | 384000 | nan             | 1.0 |
| 0.0           | 7.23  | 392000 | nan             | 1.0 |
| 0.0           | 7.38  | 400000 | nan             | 1.0 |
| 0.0           | 7.52  | 408000 | nan             | 1.0 |
| 0.0           | 7.67  | 416000 | nan             | 1.0 |
| 0.0           | 7.82  | 424000 | nan             | 1.0 |
| 0.0           | 7.97  | 432000 | nan             | 1.0 |
| 0.0           | 8.11  | 440000 | nan             | 1.0 |
| 0.0           | 8.26  | 448000 | nan             | 1.0 |
| 0.0           | 8.41  | 456000 | nan             | 1.0 |
| 0.0           | 8.56  | 464000 | nan             | 1.0 |
| 0.0           | 8.7   | 472000 | nan             | 1.0 |
| 0.0           | 8.85  | 480000 | nan             | 1.0 |
| 0.0           | 9.0   | 488000 | nan             | 1.0 |
| 0.0           | 9.15  | 496000 | nan             | 1.0 |
| 0.0           | 9.29  | 504000 | nan             | 1.0 |
| 0.0           | 9.44  | 512000 | nan             | 1.0 |
| 0.0           | 9.59  | 520000 | nan             | 1.0 |
| 0.0           | 9.74  | 528000 | nan             | 1.0 |
| 0.0           | 9.88  | 536000 | nan             | 1.0 |


### Framework versions

- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3