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# common8

This model is a fine-tuned version of [wghts/checkpoint-20000](https://huggingface.co/wghts/checkpoint-20000) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - FA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3174
- Wer: 0.3022

## 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: 1e-06
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 6
- 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: 250.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer    |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 3.5847        | 1.93   | 500   | 3.5104          | 1.0    |
| 2.7858        | 3.86   | 1000  | 2.9601          | 1.0001 |
| 1.6827        | 5.79   | 1500  | 0.7853          | 0.7030 |
| 1.4656        | 7.72   | 2000  | 0.6076          | 0.6014 |
| 1.3693        | 9.65   | 2500  | 0.5114          | 0.5307 |
| 1.379         | 11.58  | 3000  | 0.4666          | 0.4940 |
| 1.2832        | 13.51  | 3500  | 0.4257          | 0.4593 |
| 1.1931        | 15.44  | 4000  | 0.4039          | 0.4427 |
| 1.2911        | 17.37  | 4500  | 0.3956          | 0.4295 |
| 1.1577        | 19.3   | 5000  | 0.3705          | 0.4114 |
| 1.1135        | 21.24  | 5500  | 0.3740          | 0.4010 |
| 1.19          | 23.17  | 6000  | 0.3611          | 0.3935 |
| 1.1008        | 25.1   | 6500  | 0.3503          | 0.3880 |
| 1.0805        | 27.03  | 7000  | 0.3427          | 0.3781 |
| 1.1556        | 28.96  | 7500  | 0.3442          | 0.3727 |
| 1.0596        | 30.89  | 8000  | 0.3398          | 0.3646 |
| 1.0219        | 32.82  | 8500  | 0.3312          | 0.3660 |
| 1.1042        | 34.75  | 9000  | 0.3287          | 0.3612 |
| 1.0273        | 36.68  | 9500  | 0.3236          | 0.3556 |
| 1.0383        | 38.61  | 10000 | 0.3217          | 0.3558 |
| 1.0498        | 40.54  | 10500 | 0.3205          | 0.3520 |
| 0.9969        | 42.47  | 11000 | 0.3125          | 0.3504 |
| 1.0658        | 44.4   | 11500 | 0.3120          | 0.3493 |
| 0.992         | 46.33  | 12000 | 0.3137          | 0.3476 |
| 0.9737        | 48.26  | 12500 | 0.3085          | 0.3413 |
| 1.0817        | 50.19  | 13000 | 0.3091          | 0.3418 |
| 0.9414        | 52.12  | 13500 | 0.3072          | 0.3344 |
| 0.9295        | 54.05  | 14000 | 0.3039          | 0.3322 |
| 1.0248        | 55.98  | 14500 | 0.2991          | 0.3325 |
| 0.9474        | 57.91  | 15000 | 0.3032          | 0.3348 |
| 0.928         | 59.85  | 15500 | 0.2999          | 0.3285 |
| 1.0321        | 61.78  | 16000 | 0.2982          | 0.3253 |
| 0.9255        | 63.71  | 16500 | 0.2970          | 0.3231 |
| 0.8928        | 65.64  | 17000 | 0.2993          | 0.3250 |
| 1.008         | 67.57  | 17500 | 0.2985          | 0.3222 |
| 0.9371        | 69.5   | 18000 | 0.2968          | 0.3216 |
| 0.9077        | 71.43  | 18500 | 0.3011          | 0.3299 |
| 1.0044        | 73.36  | 19000 | 0.3053          | 0.3306 |
| 0.9625        | 75.29  | 19500 | 0.3159          | 0.3295 |
| 0.9816        | 77.22  | 20000 | 0.3080          | 0.3304 |
| 0.9587        | 119.19 | 20500 | 0.3088          | 0.3284 |
| 0.9178        | 122.09 | 21000 | 0.3132          | 0.3320 |
| 1.0282        | 125.0  | 21500 | 0.3099          | 0.3266 |
| 0.9337        | 127.9  | 22000 | 0.3110          | 0.3317 |
| 0.8822        | 130.81 | 22500 | 0.3037          | 0.3247 |
| 0.9644        | 133.72 | 23000 | 0.3037          | 0.3238 |
| 0.9214        | 136.62 | 23500 | 0.3040          | 0.3234 |
| 0.9167        | 139.53 | 24000 | 0.3079          | 0.3203 |
| 0.9047        | 142.44 | 24500 | 0.3018          | 0.3177 |
| 0.8909        | 145.35 | 25000 | 0.3053          | 0.3181 |
| 0.9646        | 148.25 | 25500 | 0.3095          | 0.3229 |
| 0.8802        | 151.16 | 26000 | 0.3111          | 0.3192 |
| 0.8411        | 154.07 | 26500 | 0.3068          | 0.3123 |
| 0.9235        | 156.97 | 27000 | 0.3090          | 0.3177 |
| 0.8943        | 159.88 | 27500 | 0.3115          | 0.3179 |
| 0.8854        | 162.79 | 28000 | 0.3052          | 0.3157 |
| 0.8734        | 165.69 | 28500 | 0.3077          | 0.3124 |
| 0.8515        | 168.6  | 29000 | 0.3117          | 0.3128 |
| 0.912         | 171.51 | 29500 | 0.3039          | 0.3121 |
| 0.8669        | 174.42 | 30000 | 0.3120          | 0.3123 |
| 0.823         | 177.32 | 30500 | 0.3148          | 0.3118 |
| 0.9129        | 180.23 | 31000 | 0.3179          | 0.3101 |
| 0.8255        | 183.14 | 31500 | 0.3164          | 0.3114 |
| 0.8948        | 186.05 | 32000 | 0.3128          | 0.3101 |
| 0.8397        | 188.95 | 32500 | 0.3143          | 0.3068 |
| 0.8341        | 191.86 | 33000 | 0.3127          | 0.3136 |
| 0.873         | 194.76 | 33500 | 0.3149          | 0.3124 |
| 0.8232        | 197.67 | 34000 | 0.3166          | 0.3086 |
| 0.8002        | 200.58 | 34500 | 0.3149          | 0.3061 |
| 0.8621        | 203.49 | 35000 | 0.3160          | 0.3093 |
| 0.8123        | 206.39 | 35500 | 0.3141          | 0.3063 |
| 0.7995        | 209.3  | 36000 | 0.3174          | 0.3075 |
| 0.8271        | 212.21 | 36500 | 0.3173          | 0.3043 |
| 0.8059        | 215.12 | 37000 | 0.3176          | 0.3079 |
| 0.8835        | 218.02 | 37500 | 0.3169          | 0.3062 |
| 0.8027        | 220.93 | 38000 | 0.3203          | 0.3098 |
| 0.775         | 223.83 | 38500 | 0.3159          | 0.3068 |
| 0.8487        | 226.74 | 39000 | 0.3161          | 0.3072 |
| 0.7929        | 229.65 | 39500 | 0.3143          | 0.3037 |
| 0.7653        | 232.56 | 40000 | 0.3160          | 0.3048 |
| 0.8211        | 235.46 | 40500 | 0.3173          | 0.3031 |
| 0.7761        | 238.37 | 41000 | 0.3176          | 0.3025 |
| 0.7761        | 241.28 | 41500 | 0.3179          | 0.3027 |
| 0.7903        | 244.19 | 42000 | 0.3181          | 0.3016 |
| 0.7807        | 247.09 | 42500 | 0.3170          | 0.3027 |
| 0.8406        | 250.0  | 43000 | 0.3174          | 0.3022 |


### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2
- Datasets 1.18.3.dev0
- Tokenizers 0.10.3

{"language": ["fa"], "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer"], "datasets": ["common_voice"], "model-index": [{"name": "common8", "results": []}]}
transformers pytorch wav2vec2 automatic-speech-recognition mozilla-foundation/common_voice_8_0 generated_from_trainer fa dataset:common_voice endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #fa #dataset-common_voice #endpoints_compatible #region-us 

common8
=======


This model is a fine-tuned version of wghts/checkpoint-20000 on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - FA dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3174
* Wer: 0.3022


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: 1e-06
* train\_batch\_size: 32
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 6
* 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: 250.0
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2
* Datasets 1.18.3.dev0
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-06
* train\_batch\_size: 32
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 6
* 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: 250.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2
* Datasets 1.18.3.dev0
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #fa #dataset-common_voice #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-06
* train\_batch\_size: 32
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 6
* 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: 250.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2
* Datasets 1.18.3.dev0
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #fa #dataset-common_voice #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-06
* train\_batch\_size: 32
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 6
* 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: 250.0
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2
* Datasets 1.18.3.dev0
* Tokenizers 0.10.3