      
# 

This model is a fine-tuned version of [cahya/wav2vec2-base-turkish-artificial-cv](https://huggingface.co/cahya/wav2vec2-base-turkish-artificial-cv) on the COMMON_VOICE - TR dataset.
It achieves the following results on the evaluation set:

 
|     | Dataset                       | WER     | CER      |
|---|-------------------------------|---------|----------|
| 1   | Common Voice 6.1              |  9.437  |  3.325   |
| 2   | Common Voice 7.0              |  8.147  |  2.802   |
| 3   | Common Voice 8.0              |  8.335  |  2.336   |
| 4   | Speech Recognition Community  | 28.011  | 10.66    |

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data
The following datasets were used for finetuning:
 - [Common Voice 7.0 TR](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0) 'train', 'validation' and 'other' split were used for training.
 - [Media Speech](https://www.openslr.org/108/)
 - [Magic Hub](https://magichub.com/)


## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 7.5e-06
- train_batch_size: 6
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.1224        | 3.45  | 500  | 0.1641          | 0.1396 |


### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3

{"language": ["tr"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "common_voice", "generated_from_trainer", "hf-asr-leaderboard", "robust-speech-event", "tr"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "Wav2Vec2 Base Turkish by Cahya", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Common Voice 6.1", "type": "mozilla-foundation/common_voice_7_0", "args": "tr"}, "metrics": [{"type": "wer", "value": 9.437, "name": "Test WER"}, {"type": "cer", "value": 3.325, "name": "Test CER"}, {"type": "wer", "value": 8.147, "name": "Test WER"}, {"type": "cer", "value": 2.802, "name": "Test CER"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Robust Speech Event - Dev Data", "type": "speech-recognition-community-v2/dev_data", "args": "tr"}, "metrics": [{"type": "wer", "value": 28.011, "name": "Test WER"}, {"type": "cer", "value": 10.66, "name": "Test CER"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Robust Speech Event - Test Data", "type": "speech-recognition-community-v2/eval_data", "args": "tr"}, "metrics": [{"type": "wer", "value": 33.62, "name": "Test WER"}]}]}]}
transformers pytorch wav2vec2 automatic-speech-recognition common_voice generated_from_trainer hf-asr-leaderboard robust-speech-event tr dataset:mozilla-foundation/common_voice_7_0 license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #common_voice #generated_from_trainer #hf-asr-leaderboard #robust-speech-event #tr #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 


This model is a fine-tuned version of cahya/wav2vec2-base-turkish-artificial-cv on the COMMON\_VOICE - TR dataset.
It achieves the following results on the evaluation set:



Model description
-----------------


More information needed


Intended uses & limitations
---------------------------


More information needed


Training and evaluation data
----------------------------


The following datasets were used for finetuning:


* Common Voice 7.0 TR 'train', 'validation' and 'other' split were used for training.
* Media Speech
* Magic Hub


Training procedure
------------------


### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 7.5e-06
* train\_batch\_size: 6
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 24
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 2000
* num\_epochs: 5.0


### Training results



### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.1+cu102
* Datasets 1.18.2
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 7.5e-06
* train\_batch\_size: 6
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 24
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 2000
* num\_epochs: 5.0 ### Training results ### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.1+cu102
* Datasets 1.18.2
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #common_voice #generated_from_trainer #hf-asr-leaderboard #robust-speech-event #tr #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 7.5e-06
* train\_batch\_size: 6
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 24
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 2000
* num\_epochs: 5.0 ### Training results ### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.1+cu102
* Datasets 1.18.2
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #common_voice #generated_from_trainer #hf-asr-leaderboard #robust-speech-event #tr #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 7.5e-06
* train\_batch\_size: 6
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 24
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 2000
* num\_epochs: 5.0### Training results### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.1+cu102
* Datasets 1.18.2
* Tokenizers 0.10.3