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# 

This model is a fine-tuned version of [./checkpoint-1000](https://huggingface.co/./checkpoint-1000) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - TR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3282
- Wer: 0.2836

## 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: 96
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 192
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 100.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 1.0671        | 2.04  | 200   | 0.3079          | 0.2752 |
| 0.6433        | 4.08  | 400   | 0.2728          | 0.2848 |
| 0.5687        | 6.12  | 600   | 0.2882          | 0.3036 |
| 0.5355        | 8.16  | 800   | 0.2778          | 0.2920 |
| 0.5116        | 10.2  | 1000  | 0.2906          | 0.3014 |
| 0.5313        | 9.16  | 1200  | 0.2984          | 0.3273 |
| 0.4996        | 10.69 | 1400  | 0.3170          | 0.3344 |
| 0.4845        | 12.21 | 1600  | 0.3202          | 0.3634 |
| 0.5092        | 13.74 | 1800  | 0.3167          | 0.3373 |
| 0.4777        | 15.27 | 2000  | 0.3292          | 0.3386 |
| 0.4651        | 16.79 | 2200  | 0.3070          | 0.3427 |
| 0.461         | 18.32 | 2400  | 0.3149          | 0.3561 |
| 0.4481        | 19.85 | 2600  | 0.3292          | 0.3441 |
| 0.4479        | 21.37 | 2800  | 0.3142          | 0.3209 |
| 0.4305        | 22.9  | 3000  | 0.3525          | 0.3547 |
| 0.4254        | 24.43 | 3200  | 0.3414          | 0.3400 |
| 0.4066        | 25.95 | 3400  | 0.3118          | 0.3207 |
| 0.4043        | 27.48 | 3600  | 0.3418          | 0.3483 |
| 0.3985        | 29.01 | 3800  | 0.3254          | 0.3166 |
| 0.3982        | 30.53 | 4000  | 0.3306          | 0.3453 |
| 0.3929        | 32.06 | 4200  | 0.3262          | 0.3229 |
| 0.378         | 33.59 | 4400  | 0.3546          | 0.3336 |
| 0.4062        | 35.11 | 4600  | 0.3174          | 0.3457 |
| 0.3648        | 36.64 | 4800  | 0.3377          | 0.3357 |
| 0.3609        | 38.17 | 5000  | 0.3346          | 0.3520 |
| 0.3483        | 39.69 | 5200  | 0.3350          | 0.3526 |
| 0.3548        | 41.22 | 5400  | 0.3330          | 0.3406 |
| 0.3446        | 42.75 | 5600  | 0.3398          | 0.3372 |
| 0.3346        | 44.27 | 5800  | 0.3449          | 0.3288 |
| 0.3309        | 45.8  | 6000  | 0.3320          | 0.3144 |
| 0.326         | 47.33 | 6200  | 0.3400          | 0.3279 |
| 0.3189        | 48.85 | 6400  | 0.3400          | 0.3150 |
| 0.3165        | 50.38 | 6600  | 0.3359          | 0.2995 |
| 0.3132        | 51.91 | 6800  | 0.3343          | 0.3096 |
| 0.3092        | 53.44 | 7000  | 0.3224          | 0.3029 |
| 0.2995        | 54.96 | 7200  | 0.3205          | 0.2985 |
| 0.304         | 56.49 | 7400  | 0.3523          | 0.3034 |
| 0.2952        | 58.02 | 7600  | 0.3289          | 0.2934 |
| 0.2875        | 59.54 | 7800  | 0.3350          | 0.3008 |
| 0.2868        | 61.07 | 8000  | 0.3537          | 0.3227 |
| 0.2875        | 62.6  | 8200  | 0.3389          | 0.2970 |
| 0.2778        | 64.12 | 8400  | 0.3370          | 0.2960 |
| 0.2706        | 65.65 | 8600  | 0.3250          | 0.2802 |
| 0.2669        | 67.18 | 8800  | 0.3351          | 0.2903 |
| 0.2615        | 68.7  | 9000  | 0.3382          | 0.2989 |
| 0.2563        | 70.23 | 9200  | 0.3312          | 0.2975 |
| 0.2546        | 71.76 | 9400  | 0.3212          | 0.3003 |
| 0.2482        | 73.28 | 9600  | 0.3337          | 0.3091 |
| 0.2504        | 74.81 | 9800  | 0.3308          | 0.3110 |
| 0.2456        | 76.34 | 10000 | 0.3157          | 0.3118 |
| 0.2363        | 77.86 | 10200 | 0.3251          | 0.3144 |
| 0.2319        | 79.39 | 10400 | 0.3253          | 0.3038 |
| 0.2266        | 80.92 | 10600 | 0.3374          | 0.3038 |
| 0.2279        | 82.44 | 10800 | 0.3268          | 0.2964 |
| 0.2231        | 83.97 | 11000 | 0.3278          | 0.2950 |
| 0.2185        | 85.5  | 11200 | 0.3462          | 0.2981 |
| 0.2245        | 87.02 | 11400 | 0.3311          | 0.2895 |
| 0.223         | 88.55 | 11600 | 0.3325          | 0.2877 |
| 0.2121        | 90.08 | 11800 | 0.3337          | 0.2828 |
| 0.2126        | 91.6  | 12000 | 0.3325          | 0.2808 |
| 0.2027        | 93.13 | 12200 | 0.3277          | 0.2820 |
| 0.2058        | 94.66 | 12400 | 0.3308          | 0.2827 |
| 0.1991        | 96.18 | 12600 | 0.3279          | 0.2820 |
| 0.1991        | 97.71 | 12800 | 0.3300          | 0.2822 |
| 0.1986        | 99.24 | 13000 | 0.3285          | 0.2835 |


### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0

{"language": ["tr"], "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer"], "datasets": ["common_voice"], "model-index": [{"name": "", "results": []}]}
transformers pytorch wav2vec2 automatic-speech-recognition mozilla-foundation/common_voice_8_0 generated_from_trainer tr dataset:common_voice endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #tr #dataset-common_voice #endpoints_compatible #region-us 


This model is a fine-tuned version of ./checkpoint-1000 on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - TR dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3282
* Wer: 0.2836


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: 96
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 192
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 100.0
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.3
* Tokenizers 0.11.0



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 96
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 192
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 100.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.3
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #tr #dataset-common_voice #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 96
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 192
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 100.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.3
* Tokenizers 0.11.0
passage: TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #tr #dataset-common_voice #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 96
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 192
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 100.0
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.3
* Tokenizers 0.11.0