
<!-- 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-xls-r-53h-turkish-colab

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4135
- Wer: 0.3247

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 32
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 9.4875        | 0.92  | 100  | 3.5328          | 1.0    |
| 3.1866        | 1.83  | 200  | 3.0955          | 1.0    |
| 2.027         | 2.75  | 300  | 0.9002          | 0.7685 |
| 0.7285        | 3.67  | 400  | 0.6279          | 0.6693 |
| 0.4693        | 4.59  | 500  | 0.5672          | 0.5643 |
| 0.3615        | 5.5   | 600  | 0.4995          | 0.5094 |
| 0.2846        | 6.42  | 700  | 0.4561          | 0.4797 |
| 0.2253        | 7.34  | 800  | 0.4742          | 0.4675 |
| 0.2004        | 8.26  | 900  | 0.4462          | 0.4345 |
| 0.173         | 9.17  | 1000 | 0.4688          | 0.4333 |
| 0.1547        | 10.09 | 1100 | 0.4429          | 0.4206 |
| 0.1444        | 11.01 | 1200 | 0.4662          | 0.4144 |
| 0.1274        | 11.93 | 1300 | 0.4675          | 0.4213 |
| 0.1164        | 12.84 | 1400 | 0.4947          | 0.4073 |
| 0.1081        | 13.76 | 1500 | 0.4223          | 0.3915 |
| 0.1025        | 14.68 | 1600 | 0.4493          | 0.3912 |
| 0.0944        | 15.6  | 1700 | 0.4527          | 0.3848 |
| 0.0943        | 16.51 | 1800 | 0.4288          | 0.3810 |
| 0.0885        | 17.43 | 1900 | 0.4313          | 0.3670 |
| 0.0781        | 18.35 | 2000 | 0.4729          | 0.3790 |
| 0.0828        | 19.27 | 2100 | 0.4560          | 0.3651 |
| 0.0753        | 20.18 | 2200 | 0.4478          | 0.3599 |
| 0.0702        | 21.1  | 2300 | 0.4518          | 0.3595 |
| 0.0666        | 22.02 | 2400 | 0.4080          | 0.3489 |
| 0.0661        | 22.94 | 2500 | 0.4414          | 0.3507 |
| 0.0607        | 23.85 | 2600 | 0.4209          | 0.3538 |
| 0.058         | 24.77 | 2700 | 0.4302          | 0.3382 |
| 0.0596        | 25.69 | 2800 | 0.3939          | 0.3328 |
| 0.052         | 26.61 | 2900 | 0.4374          | 0.3311 |
| 0.0473        | 27.52 | 3000 | 0.4406          | 0.3363 |
| 0.0483        | 28.44 | 3100 | 0.4272          | 0.3286 |
| 0.049         | 29.36 | 3200 | 0.4189          | 0.3257 |
| 0.0433        | 30.28 | 3300 | 0.4242          | 0.3229 |
| 0.0438        | 31.19 | 3400 | 0.4135          | 0.3247 |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.10.0+cu113
- Datasets 1.18.3
- Tokenizers 0.10.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["common_voice"], "model-index": [{"name": "wav2vec2-large-xls-r-53h-turkish-colab", "results": []}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition generated_from_trainer dataset:common_voice license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us 

wav2vec2-large-xls-r-53h-turkish-colab
======================================


This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the common\_voice dataset.
It achieves the following results on the evaluation set:


* Loss: 0.4135
* Wer: 0.3247


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: 0.0003
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 32
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.0+cu113
* Datasets 1.18.3
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 32
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.0+cu113
* Datasets 1.18.3
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 32
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.0+cu113
* Datasets 1.18.3
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 32
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.0+cu113
* Datasets 1.18.3
* Tokenizers 0.10.3