---
base_model: facebook/w2v-bert-2.0
datasets:
- common_voice_17_0
license: mit
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-bert-turkish
  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-bert-turkish

This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3552

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 8
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss |
|:-------------:|:-------:|:-----:|:---------------:|
| 1.0927        | 0.1724  | 1000  | 0.6278          |
| 0.4967        | 0.3448  | 2000  | 0.5884          |
| 0.3964        | 0.5172  | 3000  | 0.4851          |
| 0.355         | 0.6895  | 4000  | 0.5371          |
| 0.3264        | 0.8619  | 5000  | 0.4579          |
| 0.2979        | 1.0343  | 6000  | 0.4308          |
| 0.2568        | 1.2067  | 7000  | 0.4136          |
| 0.2495        | 1.3791  | 8000  | 0.4711          |
| 0.2422        | 1.5515  | 9000  | 0.4280          |
| 0.2357        | 1.7238  | 10000 | 0.4045          |
| 0.2193        | 1.8962  | 11000 | 0.4194          |
| 0.2087        | 2.0686  | 12000 | 0.4427          |
| 0.1819        | 2.2410  | 13000 | 0.4155          |
| 0.1772        | 2.4134  | 14000 | 0.4012          |
| 0.1739        | 2.5858  | 15000 | 0.3651          |
| 0.172         | 2.7581  | 16000 | 0.4081          |
| 0.1676        | 2.9305  | 17000 | 0.3948          |
| 0.1498        | 3.1029  | 18000 | 0.3587          |
| 0.1299        | 3.2753  | 19000 | 0.4106          |
| 0.1319        | 3.4477  | 20000 | 0.3624          |
| 0.1425        | 3.6201  | 21000 | 0.3551          |
| 0.1362        | 3.7924  | 22000 | 0.3504          |
| 0.1386        | 3.9648  | 23000 | 0.3454          |
| 0.1106        | 4.1372  | 24000 | 0.3632          |
| 0.1069        | 4.3096  | 25000 | 0.3404          |
| 0.1155        | 4.4820  | 26000 | 0.3517          |
| 0.1162        | 4.6544  | 27000 | 0.3315          |
| 0.1121        | 4.8268  | 28000 | 0.3521          |
| 0.1109        | 4.9991  | 29000 | 0.3456          |
| 0.0875        | 5.1715  | 30000 | 0.3507          |
| 0.0963        | 5.3439  | 31000 | 0.3878          |
| 0.0933        | 5.5163  | 32000 | 0.3653          |
| 0.0988        | 5.6887  | 33000 | 0.3427          |
| 0.0912        | 5.8611  | 34000 | 0.3582          |
| 0.0889        | 6.0334  | 35000 | 0.3262          |
| 0.0769        | 6.2058  | 36000 | 0.3548          |
| 0.08          | 6.3782  | 37000 | 0.4327          |
| 0.0821        | 6.5506  | 38000 | 0.3374          |
| 0.0841        | 6.7230  | 39000 | 0.3522          |
| 0.0826        | 6.8954  | 40000 | 0.3499          |
| 0.0773        | 7.0677  | 41000 | 0.3434          |
| 0.07          | 7.2401  | 42000 | 0.3453          |
| 0.0695        | 7.4125  | 43000 | 0.3455          |
| 0.073         | 7.5849  | 44000 | 0.3614          |
| 0.0705        | 7.7573  | 45000 | 0.3209          |
| 0.0759        | 7.9297  | 46000 | 0.3455          |
| 0.0599        | 8.1021  | 47000 | 0.3237          |
| 0.0617        | 8.2744  | 48000 | 0.3298          |
| 0.0605        | 8.4468  | 49000 | 0.3684          |
| 0.0594        | 8.6192  | 50000 | 0.3623          |
| 0.0631        | 8.7916  | 51000 | 0.3582          |
| 0.0625        | 8.9640  | 52000 | 0.3469          |
| 0.0504        | 9.1364  | 53000 | 0.3462          |
| 0.0502        | 9.3087  | 54000 | 0.3417          |
| 0.0551        | 9.4811  | 55000 | 0.3526          |
| 0.0548        | 9.6535  | 56000 | 0.3359          |
| 0.0563        | 9.8259  | 57000 | 0.3581          |
| 0.056         | 9.9983  | 58000 | 0.3421          |
| 0.042         | 10.1707 | 59000 | 0.3349          |
| 0.05          | 10.3430 | 60000 | 0.3552          |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1