---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: wav2vec2-large-mms-1b-turkish-colab
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_11_0
      type: common_voice_11_0
      config: tr
      split: test
      args: tr
    metrics:
    - name: Wer
      type: wer
      value: 0.2274112463363031
---

<!-- 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-turkish-colab

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1588
- Wer: 0.2274

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 7.9572        | 0.09  | 100  | 0.2279          | 0.2821 |
| 0.316         | 0.18  | 200  | 0.2011          | 0.2632 |
| 0.282         | 0.27  | 300  | 0.2027          | 0.2555 |
| 0.285         | 0.35  | 400  | 0.1978          | 0.2580 |
| 0.2741        | 0.44  | 500  | 0.1956          | 0.2596 |
| 0.2643        | 0.53  | 600  | 0.1790          | 0.2487 |
| 0.2758        | 0.62  | 700  | 0.1791          | 0.2463 |
| 0.2766        | 0.71  | 800  | 0.1791          | 0.2499 |
| 0.2733        | 0.8   | 900  | 0.1854          | 0.2610 |
| 0.2611        | 0.89  | 1000 | 0.1793          | 0.2464 |
| 0.2582        | 0.97  | 1100 | 0.1734          | 0.2460 |
| 0.2421        | 1.06  | 1200 | 0.1711          | 0.2408 |
| 0.2424        | 1.15  | 1300 | 0.1737          | 0.2434 |
| 0.2455        | 1.24  | 1400 | 0.1761          | 0.2489 |
| 0.2588        | 1.33  | 1500 | 0.1720          | 0.2410 |
| 0.2591        | 1.42  | 1600 | 0.1761          | 0.2444 |
| 0.2497        | 1.51  | 1700 | 0.1696          | 0.2381 |
| 0.254         | 1.59  | 1800 | 0.1728          | 0.2391 |
| 0.2479        | 1.68  | 1900 | 0.1724          | 0.2402 |
| 0.2395        | 1.77  | 2000 | 0.1726          | 0.2389 |
| 0.237         | 1.86  | 2100 | 0.1710          | 0.2378 |
| 0.2427        | 1.95  | 2200 | 0.1682          | 0.2348 |
| 0.2399        | 2.04  | 2300 | 0.1699          | 0.2371 |
| 0.2457        | 2.13  | 2400 | 0.1695          | 0.2357 |
| 0.2432        | 2.21  | 2500 | 0.1707          | 0.2387 |
| 0.229         | 2.3   | 2600 | 0.1687          | 0.2324 |
| 0.2413        | 2.39  | 2700 | 0.1681          | 0.2354 |
| 0.2286        | 2.48  | 2800 | 0.1664          | 0.2329 |
| 0.2405        | 2.57  | 2900 | 0.1646          | 0.2337 |
| 0.2266        | 2.66  | 3000 | 0.1668          | 0.2341 |
| 0.2337        | 2.75  | 3100 | 0.1642          | 0.2325 |
| 0.233         | 2.83  | 3200 | 0.1635          | 0.2301 |
| 0.2235        | 2.92  | 3300 | 0.1639          | 0.2342 |
| 0.2395        | 3.01  | 3400 | 0.1630          | 0.2305 |
| 0.2165        | 3.1   | 3500 | 0.1622          | 0.2305 |
| 0.2258        | 3.19  | 3600 | 0.1617          | 0.2296 |
| 0.2288        | 3.28  | 3700 | 0.1608          | 0.2307 |
| 0.218         | 3.37  | 3800 | 0.1610          | 0.2301 |
| 0.2242        | 3.45  | 3900 | 0.1604          | 0.2304 |
| 0.2248        | 3.54  | 4000 | 0.1603          | 0.2273 |
| 0.2223        | 3.63  | 4100 | 0.1595          | 0.2282 |
| 0.2161        | 3.72  | 4200 | 0.1593          | 0.2283 |
| 0.2281        | 3.81  | 4300 | 0.1592          | 0.2278 |
| 0.2236        | 3.9   | 4400 | 0.1593          | 0.2281 |
| 0.2277        | 3.99  | 4500 | 0.1588          | 0.2274 |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3