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# wav2vec2-common_voice-tr-demo

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 - TR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3815
- Wer: 0.3493

## 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: 15.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 0.92  | 100  | 3.5559          | 1.0    |
| No log        | 1.83  | 200  | 3.0161          | 0.9999 |
| No log        | 2.75  | 300  | 0.8587          | 0.7443 |
| No log        | 3.67  | 400  | 0.5855          | 0.6121 |
| 3.1095        | 4.59  | 500  | 0.4841          | 0.5204 |
| 3.1095        | 5.5   | 600  | 0.4533          | 0.4923 |
| 3.1095        | 6.42  | 700  | 0.4157          | 0.4342 |
| 3.1095        | 7.34  | 800  | 0.4304          | 0.4334 |
| 3.1095        | 8.26  | 900  | 0.4097          | 0.4068 |
| 0.2249        | 9.17  | 1000 | 0.4049          | 0.3881 |
| 0.2249        | 10.09 | 1100 | 0.3993          | 0.3809 |
| 0.2249        | 11.01 | 1200 | 0.3855          | 0.3782 |
| 0.2249        | 11.93 | 1300 | 0.3923          | 0.3713 |
| 0.2249        | 12.84 | 1400 | 0.3833          | 0.3591 |
| 0.1029        | 13.76 | 1500 | 0.3811          | 0.3570 |
| 0.1029        | 14.68 | 1600 | 0.3834          | 0.3499 |


### Framework versions

- Transformers 4.13.0.dev0
- Pytorch 1.12.0a0+2c916ef
- Datasets 2.2.2
- Tokenizers 0.10.3

{"language": ["tr"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "common_voice", "generated_from_trainer"], "datasets": ["common_voice"], "model-index": [{"name": "wav2vec2-common_voice-tr-demo", "results": []}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition common_voice generated_from_trainer tr dataset:common_voice license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #common_voice #generated_from_trainer #tr #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us 

wav2vec2-common\_voice-tr-demo
==============================


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


* Loss: 0.3815
* Wer: 0.3493


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: 15.0


### Training results



### Framework versions


* Transformers 4.13.0.dev0
* Pytorch 1.12.0a0+2c916ef
* Datasets 2.2.2
* 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: 15.0 ### Training results ### Framework versions


* Transformers 4.13.0.dev0
* Pytorch 1.12.0a0+2c916ef
* Datasets 2.2.2
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #common_voice #generated_from_trainer #tr #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: 15.0 ### Training results ### Framework versions


* Transformers 4.13.0.dev0
* Pytorch 1.12.0a0+2c916ef
* Datasets 2.2.2
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #common_voice #generated_from_trainer #tr #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: 15.0### Training results### Framework versions


* Transformers 4.13.0.dev0
* Pytorch 1.12.0a0+2c916ef
* Datasets 2.2.2
* Tokenizers 0.10.3