---
language:
- vot
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- vot
- robust-speech-event
- model_for_talk
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-vot-final-a2
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 8
      type: mozilla-foundation/common_voice_8_0
      args: vot
    metrics:
       - name: Test WER
         type: wer
         value: []
       - name: Test CER
         type: cer
         value: []
---

<!-- 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-300m-vot-final-a2

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - VOT dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8745
- Wer: 0.8333

## 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: 0.0004
- 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: 340
- num_epochs: 200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 11.1216       | 33.33  | 100  | 4.2848          | 1.0    |
| 2.9982        | 66.67  | 200  | 2.8665          | 1.0    |
| 1.5476        | 100.0  | 300  | 2.3022          | 0.8889 |
| 0.2776        | 133.33 | 400  | 2.7480          | 0.8889 |
| 0.1136        | 166.67 | 500  | 2.5383          | 0.8889 |
| 0.0489        | 200.0  | 600  | 2.8745          | 0.8333 |

### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0


---
language:
- sat
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- sat
- robust-speech-event
- model_for_talk
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-sat-final
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 8
      type: mozilla-foundation/common_voice_8_0
      args: sat
    metrics:
       - name: Test WER
         type: wer
         value: 0.3493975903614458
       - name: Test CER
         type: cer
         value: 0.13773314203730272
---

<!-- 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-300m-sat-final

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - SAT dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8012
- Wer: 0.3815

## 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: 0.0004
- 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: 170
- num_epochs: 200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 10.6317       | 33.29  | 100  | 2.8629          | 1.0    |
| 2.047         | 66.57  | 200  | 0.9516          | 0.5703 |
| 0.4475        | 99.86  | 300  | 0.8539          | 0.3896 |
| 0.0716        | 133.29 | 400  | 0.8277          | 0.3454 |
| 0.047         | 166.57 | 500  | 0.7597          | 0.3655 |
| 0.0249        | 199.86 | 600  | 0.8012          | 0.3815 |

### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0


---
language:
- hi
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_7_0
- generated_from_trainer
- hi
- robust-speech-event
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-hi-CV7
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 7
      type: mozilla-foundation/common_voice_7_0
      args: hi
    metrics:
       - name: Test WER
         type: wer
         value: []
       - name: Test CER
         type: cer
         value: []
---

<!-- 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-300m-hi-test123

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - HI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6588
- Wer: 0.2987

## 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:
#
- 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: 2000
- num_epochs: 60
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 12.809        | 1.36  | 200  | 6.2066          | 1.0    |
| 4.3402        | 2.72  | 400  | 3.5184          | 1.0    |
| 3.4365        | 4.08  | 600  | 3.2779          | 1.0    |
| 1.8643        | 5.44  | 800  | 0.9875          | 0.6270 |
| 0.7504        | 6.8   | 1000 | 0.6382          | 0.4666 |
| 0.5328        | 8.16  | 1200 | 0.6075          | 0.4505 |
| 0.4364        | 9.52  | 1400 | 0.5785          | 0.4215 |
| 0.3777        | 10.88 | 1600 | 0.6279          | 0.4227 |
| 0.3374        | 12.24 | 1800 | 0.6536          | 0.4192 |
| 0.3236        | 13.6  | 2000 | 0.5911          | 0.4047 |
| 0.2877        | 14.96 | 2200 | 0.5955          | 0.4097 |
| 0.2643        | 16.33 | 2400 | 0.5923          | 0.3744 |
| 0.2421        | 17.68 | 2600 | 0.6307          | 0.3814 |
| 0.2218        | 19.05 | 2800 | 0.6036          | 0.3764 |
| 0.2046        | 20.41 | 3000 | 0.6286          | 0.3797 |
| 0.191         | 21.77 | 3200 | 0.6517          | 0.3889 |
| 0.1856        | 23.13 | 3400 | 0.6193          | 0.3661 |
| 0.1721        | 24.49 | 3600 | 0.7034          | 0.3727 |
| 0.1656        | 25.85 | 3800 | 0.6293          | 0.3591 |
| 0.1532        | 27.21 | 4000 | 0.6075          | 0.3611 |
| 0.1507        | 28.57 | 4200 | 0.6313          | 0.3565 |
| 0.1381        | 29.93 | 4400 | 0.6564          | 0.3578 |
| 0.1359        | 31.29 | 4600 | 0.6724          | 0.3543 |
| 0.1248        | 32.65 | 4800 | 0.6789          | 0.3512 |
| 0.1198        | 34.01 | 5000 | 0.6442          | 0.3539 |
| 0.1125        | 35.37 | 5200 | 0.6676          | 0.3419 |
| 0.1036        | 36.73 | 5400 | 0.7017          | 0.3435 |
| 0.0982        | 38.09 | 5600 | 0.6828          | 0.3319 |
| 0.0971        | 39.45 | 5800 | 0.6112          | 0.3351 |
| 0.0968        | 40.81 | 6000 | 0.6424          | 0.3252 |
| 0.0893        | 42.18 | 6200 | 0.6707          | 0.3304 |
| 0.0878        | 43.54 | 6400 | 0.6432          | 0.3236 |
| 0.0827        | 44.89 | 6600 | 0.6696          | 0.3240 |
| 0.0788        | 46.26 | 6800 | 0.6564          | 0.3180 |
| 0.0753        | 47.62 | 7000 | 0.6574          | 0.3130 |
| 0.0674        | 48.98 | 7200 | 0.6698          | 0.3175 |
| 0.0676        | 50.34 | 7400 | 0.6441          | 0.3142 |
| 0.0626        | 51.7  | 7600 | 0.6642          | 0.3121 |
| 0.0617        | 53.06 | 7800 | 0.6615          | 0.3117 |
| 0.0599        | 54.42 | 8000 | 0.6634          | 0.3059 |
| 0.0538        | 55.78 | 8200 | 0.6464          | 0.3033 |
| 0.0571        | 57.14 | 8400 | 0.6503          | 0.3018 |
| 0.0491        | 58.5  | 8600 | 0.6625          | 0.3025 |
| 0.0511        | 59.86 | 8800 | 0.6588          | 0.2987 |

### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0


---
language:
- mt
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- mt
- robust-speech-event
- model_for_talk
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-maltese
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 8
      type: mozilla-foundation/common_voice_8_0
      args: mt
---

<!-- 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-300m-maltese

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - MT dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2994
- Wer: 0.2781

## 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: 7e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1800
- num_epochs: 100.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.0174        | 9.01  | 1000  | 3.0552          | 1.0    |
| 1.0446        | 18.02 | 2000  | 0.6708          | 0.7577 |
| 0.7995        | 27.03 | 3000  | 0.4202          | 0.4770 |
| 0.6978        | 36.04 | 4000  | 0.3054          | 0.3494 |
| 0.6189        | 45.05 | 5000  | 0.2878          | 0.3154 |
| 0.5667        | 54.05 | 6000  | 0.3114          | 0.3286 |
| 0.5173        | 63.06 | 7000  | 0.3085          | 0.3021 |
| 0.4682        | 72.07 | 8000  | 0.3058          | 0.2969 |
| 0.451         | 81.08 | 9000  | 0.3146          | 0.2907 |
| 0.4213        | 90.09 | 10000 | 0.3030          | 0.2881 |
| 0.4005        | 99.1  | 11000 | 0.3001          | 0.2789 |

### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0

### Evaluation Script

!python eval.py \
    --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-maltese \
    --dataset mozilla-foundation/common_voice_8_0 --config mt --split test --log_outputs


---
language:
- hi
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- hi
- robust-speech-event
- model_for_talk
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-hi-with-LM-v1
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 8
      type: mozilla-foundation/common_voice_8_0
      args: hi
    metrics:
       - name: Test WER
         type: wer
         value: []
       - name: Test CER
         type: cer
         value: []
---

<!-- 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-300m-hi-cv8

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - HI  dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6510
- Wer: 0.3179

## 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:

- 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: 2000
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 12.5576       | 1.04  | 200  | 6.6594          | 1.0    |
| 4.4069        | 2.07  | 400  | 3.6011          | 1.0    |
| 3.4273        | 3.11  | 600  | 3.3370          | 1.0    |
| 2.1108        | 4.15  | 800  | 1.0641          | 0.6562 |
| 0.8817        | 5.18  | 1000 | 0.7178          | 0.5172 |
| 0.6508        | 6.22  | 1200 | 0.6612          | 0.4839 |
| 0.5524        | 7.25  | 1400 | 0.6458          | 0.4889 |
| 0.4992        | 8.29  | 1600 | 0.5791          | 0.4382 |
| 0.4669        | 9.33  | 1800 | 0.6039          | 0.4352 |
| 0.4441        | 10.36 | 2000 | 0.6276          | 0.4297 |
| 0.4172        | 11.4  | 2200 | 0.6183          | 0.4474 |
| 0.3872        | 12.44 | 2400 | 0.5886          | 0.4231 |
| 0.3692        | 13.47 | 2600 | 0.6448          | 0.4399 |
| 0.3385        | 14.51 | 2800 | 0.6344          | 0.4075 |
| 0.3246        | 15.54 | 3000 | 0.5896          | 0.4087 |
| 0.3026        | 16.58 | 3200 | 0.6158          | 0.4016 |
| 0.284         | 17.62 | 3400 | 0.6038          | 0.3906 |
| 0.2682        | 18.65 | 3600 | 0.6165          | 0.3900 |
| 0.2577        | 19.69 | 3800 | 0.5754          | 0.3805 |
| 0.2509        | 20.73 | 4000 | 0.6028          | 0.3925 |
| 0.2426        | 21.76 | 4200 | 0.6335          | 0.4138 |
| 0.2346        | 22.8  | 4400 | 0.6128          | 0.3870 |
| 0.2205        | 23.83 | 4600 | 0.6223          | 0.3831 |
| 0.2104        | 24.87 | 4800 | 0.6122          | 0.3781 |
| 0.1992        | 25.91 | 5000 | 0.6467          | 0.3792 |
| 0.1916        | 26.94 | 5200 | 0.6277          | 0.3636 |
| 0.1835        | 27.98 | 5400 | 0.6317          | 0.3773 |
| 0.1776        | 29.02 | 5600 | 0.6124          | 0.3614 |
| 0.1751        | 30.05 | 5800 | 0.6475          | 0.3628 |
| 0.1662        | 31.09 | 6000 | 0.6266          | 0.3504 |
| 0.1584        | 32.12 | 6200 | 0.6347          | 0.3532 |
| 0.1494        | 33.16 | 6400 | 0.6636          | 0.3491 |
| 0.1457        | 34.2  | 6600 | 0.6334          | 0.3507 |
| 0.1427        | 35.23 | 6800 | 0.6397          | 0.3442 |
| 0.1397        | 36.27 | 7000 | 0.6468          | 0.3496 |
| 0.1283        | 37.31 | 7200 | 0.6291          | 0.3416 |
| 0.1255        | 38.34 | 7400 | 0.6652          | 0.3461 |
| 0.1195        | 39.38 | 7600 | 0.6587          | 0.3342 |
| 0.1169        | 40.41 | 7800 | 0.6478          | 0.3319 |
| 0.1126        | 41.45 | 8000 | 0.6280          | 0.3291 |
| 0.1112        | 42.49 | 8200 | 0.6434          | 0.3290 |
| 0.1069        | 43.52 | 8400 | 0.6542          | 0.3268 |
| 0.1027        | 44.56 | 8600 | 0.6536          | 0.3239 |
| 0.0993        | 45.6  | 8800 | 0.6622          | 0.3257 |
| 0.0973        | 46.63 | 9000 | 0.6572          | 0.3192 |
| 0.0911        | 47.67 | 9200 | 0.6522          | 0.3175 |
| 0.0897        | 48.7  | 9400 | 0.6521          | 0.3200 |
| 0.0905        | 49.74 | 9600 | 0.6510          | 0.3179 |

### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0


---
language:
- pa-IN
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- pa-IN
- robust-speech-event
- model_for_talk
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: wav2vec2-xls-r-300m-pa-IN-r5
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 8
      type: mozilla-foundation/common_voice_8_0
      args: pa-IN
    metrics:
       - name: Test WER
         type: wer
         value: []
       - name: Test CER
         type: cer
         value: []
---

<!-- 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. -->

#

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - PA-IN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8881
- Wer: 0.4175

## 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: 0.000111
- train_batch_size: 16
- eval_batch_size: 32
- 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: 2000
- num_epochs: 200.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 10.695        | 18.52  | 500  | 3.5681          | 1.0    |
| 3.2718        | 37.04  | 1000 | 2.3081          | 0.9643 |
| 0.8727        | 55.56  | 1500 | 0.7227          | 0.5147 |
| 0.3349        | 74.07  | 2000 | 0.7498          | 0.4959 |
| 0.2134        | 92.59  | 2500 | 0.7779          | 0.4720 |
| 0.1445        | 111.11 | 3000 | 0.8120          | 0.4594 |
| 0.1057        | 129.63 | 3500 | 0.8225          | 0.4610 |
| 0.0826        | 148.15 | 4000 | 0.8307          | 0.4351 |
| 0.0639        | 166.67 | 4500 | 0.8967          | 0.4316 |
| 0.0528        | 185.19 | 5000 | 0.8875          | 0.4238 |

### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0


---
language:
- br
license: apache-2.0
tags:
- generated_from_trainer
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_8_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-br-with-LM
  results:
  - task:
      type: automatic-speech-recognition
      name: Speech Recognition
    dataset:
      type: mozilla-foundation/common_voice_8_0
      name: Common Voice 8
      args: br
    metrics:
      - type: wer
        value: []
        name: Test WER
      - name: Test CER
        type: cer
        value: []
---

<!-- 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-300m-br-d2

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - BR dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1257
- Wer: 0.4631

## 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: 0.00034
- 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: 750
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 14.0379       | 0.68  | 100  | 5.6808          | 1.0    |
| 3.9145        | 1.35  | 200  | 3.1970          | 1.0    |
| 3.0293        | 2.03  | 300  | 2.9513          | 1.0    |
| 2.0927        | 2.7   | 400  | 1.4545          | 0.8887 |
| 1.1556        | 3.38  | 500  | 1.0966          | 0.7564 |
| 0.9628        | 4.05  | 600  | 0.9808          | 0.7364 |
| 0.7869        | 4.73  | 700  | 1.0488          | 0.7355 |
| 0.703         | 5.41  | 800  | 0.9500          | 0.6881 |
| 0.6657        | 6.08  | 900  | 0.9309          | 0.6259 |
| 0.5663        | 6.76  | 1000 | 0.9133          | 0.6357 |
| 0.496         | 7.43  | 1100 | 0.9890          | 0.6028 |
| 0.4748        | 8.11  | 1200 | 0.9469          | 0.5894 |
| 0.4135        | 8.78  | 1300 | 0.9270          | 0.6045 |
| 0.3579        | 9.46  | 1400 | 0.8818          | 0.5708 |
| 0.353         | 10.14 | 1500 | 0.9244          | 0.5781 |
| 0.334         | 10.81 | 1600 | 0.9009          | 0.5638 |
| 0.2917        | 11.49 | 1700 | 1.0132          | 0.5828 |
| 0.29          | 12.16 | 1800 | 0.9696          | 0.5668 |
| 0.2691        | 12.84 | 1900 | 0.9811          | 0.5455 |
| 0.25          | 13.51 | 2000 | 0.9951          | 0.5624 |
| 0.2467        | 14.19 | 2100 | 0.9653          | 0.5573 |
| 0.2242        | 14.86 | 2200 | 0.9714          | 0.5378 |
| 0.2066        | 15.54 | 2300 | 0.9829          | 0.5394 |
| 0.2075        | 16.22 | 2400 | 1.0547          | 0.5520 |
| 0.1923        | 16.89 | 2500 | 1.0014          | 0.5397 |
| 0.1919        | 17.57 | 2600 | 0.9978          | 0.5477 |
| 0.1908        | 18.24 | 2700 | 1.1064          | 0.5397 |
| 0.157         | 18.92 | 2800 | 1.0629          | 0.5238 |
| 0.159         | 19.59 | 2900 | 1.0642          | 0.5321 |
| 0.1652        | 20.27 | 3000 | 1.0207          | 0.5328 |
| 0.141         | 20.95 | 3100 | 0.9948          | 0.5312 |
| 0.1417        | 21.62 | 3200 | 1.0338          | 0.5328 |
| 0.1514        | 22.3  | 3300 | 1.0513          | 0.5313 |
| 0.1365        | 22.97 | 3400 | 1.0357          | 0.5291 |
| 0.1319        | 23.65 | 3500 | 1.0587          | 0.5167 |
| 0.1298        | 24.32 | 3600 | 1.0636          | 0.5236 |
| 0.1245        | 25.0  | 3700 | 1.1367          | 0.5280 |
| 0.1114        | 25.68 | 3800 | 1.0633          | 0.5200 |
| 0.1088        | 26.35 | 3900 | 1.0495          | 0.5210 |
| 0.1175        | 27.03 | 4000 | 1.0897          | 0.5095 |
| 0.1043        | 27.7  | 4100 | 1.0580          | 0.5309 |
| 0.0951        | 28.38 | 4200 | 1.0448          | 0.5067 |
| 0.1011        | 29.05 | 4300 | 1.0665          | 0.5137 |
| 0.0889        | 29.73 | 4400 | 1.0579          | 0.5026 |
| 0.0833        | 30.41 | 4500 | 1.0740          | 0.5037 |
| 0.0889        | 31.08 | 4600 | 1.0933          | 0.5083 |
| 0.0784        | 31.76 | 4700 | 1.0715          | 0.5089 |
| 0.0767        | 32.43 | 4800 | 1.0658          | 0.5049 |
| 0.0769        | 33.11 | 4900 | 1.1118          | 0.4979 |
| 0.0722        | 33.78 | 5000 | 1.1413          | 0.4986 |
| 0.0709        | 34.46 | 5100 | 1.0706          | 0.4885 |
| 0.0664        | 35.14 | 5200 | 1.1217          | 0.4884 |
| 0.0648        | 35.81 | 5300 | 1.1298          | 0.4941 |
| 0.0657        | 36.49 | 5400 | 1.1330          | 0.4920 |
| 0.0582        | 37.16 | 5500 | 1.0598          | 0.4835 |
| 0.0602        | 37.84 | 5600 | 1.1097          | 0.4943 |
| 0.0598        | 38.51 | 5700 | 1.0976          | 0.4876 |
| 0.0547        | 39.19 | 5800 | 1.0734          | 0.4825 |
| 0.0561        | 39.86 | 5900 | 1.0926          | 0.4850 |
| 0.0516        | 40.54 | 6000 | 1.1579          | 0.4751 |
| 0.0478        | 41.22 | 6100 | 1.1384          | 0.4706 |
| 0.0396        | 41.89 | 6200 | 1.1462          | 0.4739 |
| 0.0472        | 42.57 | 6300 | 1.1277          | 0.4732 |
| 0.0447        | 43.24 | 6400 | 1.1517          | 0.4752 |
| 0.0423        | 43.92 | 6500 | 1.1219          | 0.4784 |
| 0.0426        | 44.59 | 6600 | 1.1311          | 0.4724 |
| 0.0391        | 45.27 | 6700 | 1.1135          | 0.4692 |
| 0.0362        | 45.95 | 6800 | 1.0878          | 0.4645 |
| 0.0329        | 46.62 | 6900 | 1.1137          | 0.4668 |
| 0.0356        | 47.3  | 7000 | 1.1233          | 0.4687 |
| 0.0328        | 47.97 | 7100 | 1.1238          | 0.4653 |
| 0.0323        | 48.65 | 7200 | 1.1307          | 0.4646 |
| 0.0325        | 49.32 | 7300 | 1.1242          | 0.4645 |
| 0.03          | 50.0  | 7400 | 1.1257          | 0.4631 |

### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0


---
language:
- sl
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- sl
- robust-speech-event
- model_for_talk
datasets:
- common_voice
model-index:
- name: wav2vec2-xls-r-sl-a1
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 8
      type: mozilla-foundation/common_voice_8_0
      args: sl
    metrics:
       - name: Test WER
         type: wer
         value: 0.20626555409164105
       - name: Test CER
         type: cer
         value: 0.051648321634392154
---

<!-- 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. -->

#

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - SL dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2756
- Wer: 0.2279

## 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: 7.1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 100.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.3881        | 6.1   | 500  | 2.9710          | 1.0    |
| 2.6401        | 12.2  | 1000 | 1.7677          | 0.9734 |
| 1.5152        | 18.29 | 1500 | 0.5564          | 0.6011 |
| 1.2191        | 24.39 | 2000 | 0.4319          | 0.4390 |
| 1.0237        | 30.49 | 2500 | 0.3141          | 0.3175 |
| 0.8892        | 36.59 | 3000 | 0.2748          | 0.2689 |
| 0.8296        | 42.68 | 3500 | 0.2680          | 0.2534 |
| 0.7602        | 48.78 | 4000 | 0.2820          | 0.2506 |
| 0.7186        | 54.88 | 4500 | 0.2672          | 0.2398 |
| 0.6887        | 60.98 | 5000 | 0.2729          | 0.2402 |
| 0.6507        | 67.07 | 5500 | 0.2767          | 0.2361 |
| 0.6226        | 73.17 | 6000 | 0.2817          | 0.2332 |
| 0.6024        | 79.27 | 6500 | 0.2679          | 0.2279 |
| 0.5787        | 85.37 | 7000 | 0.2837          | 0.2316 |
| 0.5744        | 91.46 | 7500 | 0.2838          | 0.2284 |
| 0.5556        | 97.56 | 8000 | 0.2763          | 0.2281 |

### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0


---
language:
- bg
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- bg
- robust-speech-event
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-bg-d2
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 8
      type: mozilla-foundation/common_voice_8_0
      args: bg
    metrics:
       - name: Test WER
         type: wer
         value: []
       - name: Test CER
         type: cer
         value: []
---

<!-- 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-300m-bg-d2

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - BG dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3421
- Wer: 0.2860

## 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: 0.00025
- 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: 700
- num_epochs: 35
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 6.8791        | 1.74  | 200  | 3.1902          | 1.0    |
| 3.0441        | 3.48  | 400  | 2.8098          | 0.9864 |
| 1.1499        | 5.22  | 600  | 0.4668          | 0.5014 |
| 0.4968        | 6.96  | 800  | 0.4162          | 0.4472 |
| 0.3553        | 8.7   | 1000 | 0.3580          | 0.3777 |
| 0.3027        | 10.43 | 1200 | 0.3422          | 0.3506 |
| 0.2562        | 12.17 | 1400 | 0.3556          | 0.3639 |
| 0.2272        | 13.91 | 1600 | 0.3621          | 0.3583 |
| 0.2125        | 15.65 | 1800 | 0.3436          | 0.3358 |
| 0.1904        | 17.39 | 2000 | 0.3650          | 0.3545 |
| 0.1695        | 19.13 | 2200 | 0.3366          | 0.3241 |
| 0.1532        | 20.87 | 2400 | 0.3550          | 0.3311 |
| 0.1453        | 22.61 | 2600 | 0.3582          | 0.3131 |
| 0.1359        | 24.35 | 2800 | 0.3524          | 0.3084 |
| 0.1233        | 26.09 | 3000 | 0.3503          | 0.2973 |
| 0.1114        | 27.83 | 3200 | 0.3434          | 0.2946 |
| 0.1051        | 29.57 | 3400 | 0.3474          | 0.2956 |
| 0.0965        | 31.3  | 3600 | 0.3426          | 0.2907 |
| 0.0923        | 33.04 | 3800 | 0.3478          | 0.2894 |
| 0.0894        | 34.78 | 4000 | 0.3421          | 0.2860 |

### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0


---
language:
- mt
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- mt
- robust-speech-event
- model_for_talk
datasets:
- common_voice
model-index:
- name: wav2vec2-xls-r-300m-mt-o1
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 8
      type: mozilla-foundation/common_voice_8_0
      args: mt
    metrics:
       - name: Test WER
         type: wer
         value: []
       - name: Test CER
         type: cer
         value: []
---

<!-- 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. -->

#

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - MT dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1987
- Wer: 0.1920

## 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: 7e-05
- train_batch_size: 32
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 100.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 1.1721        | 18.02 | 2000  | 0.3831          | 0.4066 |
| 0.7849        | 36.04 | 4000  | 0.2191          | 0.2417 |
| 0.6723        | 54.05 | 6000  | 0.2056          | 0.2134 |
| 0.6015        | 72.07 | 8000  | 0.2008          | 0.2031 |
| 0.5386        | 90.09 | 10000 | 0.1967          | 0.1953 |

### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0


---
language:
- as
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- as
- robust-speech-event
- model_for_talk
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-as-with-LM-v2
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 8
      type: mozilla-foundation/common_voice_8_0
      args: hsb
    metrics:
       - name: Test WER
         type: wer
         value: []
       - name: Test CER
         type: cer
         value: []
---

<!-- 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-300m-as-v9

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1679
- Wer: 0.5761

## 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: 0.000111
- 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: 300
- num_epochs: 200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 8.3852        | 10.51  | 200  | 3.6402          | 1.0    |
| 3.5374        | 21.05  | 400  | 3.3894          | 1.0    |
| 2.8645        | 31.56  | 600  | 1.3143          | 0.8303 |
| 1.1784        | 42.1   | 800  | 0.9417          | 0.6661 |
| 0.7805        | 52.62  | 1000 | 0.9292          | 0.6237 |
| 0.5973        | 63.15  | 1200 | 0.9489          | 0.6014 |
| 0.4784        | 73.67  | 1400 | 0.9916          | 0.5962 |
| 0.4138        | 84.21  | 1600 | 1.0272          | 0.6121 |
| 0.3491        | 94.72  | 1800 | 1.0412          | 0.5984 |
| 0.3062        | 105.26 | 2000 | 1.0769          | 0.6005 |
| 0.2707        | 115.77 | 2200 | 1.0708          | 0.5752 |
| 0.2459        | 126.31 | 2400 | 1.1285          | 0.6009 |
| 0.2234        | 136.82 | 2600 | 1.1209          | 0.5949 |
| 0.2035        | 147.36 | 2800 | 1.1348          | 0.5842 |
| 0.1876        | 157.87 | 3000 | 1.1480          | 0.5872 |
| 0.1669        | 168.41 | 3200 | 1.1496          | 0.5838 |
| 0.1595        | 178.92 | 3400 | 1.1721          | 0.5778 |
| 0.1505        | 189.46 | 3600 | 1.1654          | 0.5744 |
| 0.1486        | 199.97 | 3800 | 1.1679          | 0.5761 |

### Framework versions

- Transformers 4.16.1
- Pytorch 1.10.0+cu111
- Datasets 1.18.2
- Tokenizers 0.11.0


---
language:
- sr
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- sr
- robust-speech-event
- model_for_talk
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-sr-with-LM
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 8
      type: mozilla-foundation/common_voice_8_0
      args: sr
    metrics:
       - name: Test WER
         type: wer
         value: 0.303313
       - name: Test CER
         type: cer
         value: 0.1048951
---

<!-- 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-300m-sr-v4

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - SR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5570
- Wer: 0.3038

## 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: 800
- num_epochs: 200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 8.2934        | 7.5   | 300  | 2.9777          | 0.9995 |
| 1.5049        | 15.0  | 600  | 0.5036          | 0.4806 |
| 0.3263        | 22.5  | 900  | 0.5822          | 0.4055 |
| 0.2008        | 30.0  | 1200 | 0.5609          | 0.4032 |
| 0.1543        | 37.5  | 1500 | 0.5203          | 0.3710 |
| 0.1158        | 45.0  | 1800 | 0.6458          | 0.3985 |
| 0.0997        | 52.5  | 2100 | 0.6227          | 0.4013 |
| 0.0834        | 60.0  | 2400 | 0.6048          | 0.3836 |
| 0.0665        | 67.5  | 2700 | 0.6197          | 0.3686 |
| 0.0602        | 75.0  | 3000 | 0.5418          | 0.3453 |
| 0.0524        | 82.5  | 3300 | 0.5310          | 0.3486 |
| 0.0445        | 90.0  | 3600 | 0.5599          | 0.3374 |
| 0.0406        | 97.5  | 3900 | 0.5958          | 0.3327 |
| 0.0358        | 105.0 | 4200 | 0.6017          | 0.3262 |
| 0.0302        | 112.5 | 4500 | 0.5613          | 0.3248 |
| 0.0285        | 120.0 | 4800 | 0.5659          | 0.3462 |
| 0.0213        | 127.5 | 5100 | 0.5568          | 0.3206 |
| 0.0215        | 135.0 | 5400 | 0.6524          | 0.3472 |
| 0.0162        | 142.5 | 5700 | 0.6223          | 0.3458 |
| 0.0137        | 150.0 | 6000 | 0.6625          | 0.3313 |
| 0.0114        | 157.5 | 6300 | 0.5739          | 0.3336 |
| 0.0101        | 165.0 | 6600 | 0.5906          | 0.3285 |
| 0.008         | 172.5 | 6900 | 0.5982          | 0.3112 |
| 0.0076        | 180.0 | 7200 | 0.5399          | 0.3094 |
| 0.0071        | 187.5 | 7500 | 0.5387          | 0.2991 |
| 0.0057        | 195.0 | 7800 | 0.5570          | 0.3038 |

### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.2
- Tokenizers 0.11.0

### Evaluation Script

!python eval.py \
    --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-sr-with-LM \
    --dataset mozilla-foundation/common_voice_8_0 --config sr --split test --log_outputs


---
language:
- sl
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- sl
- robust-speech-event
- model_for_talk
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-sl-with-LM-v1
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 8
      type: mozilla-foundation/common_voice_8_0
      args: sl
    metrics:
       - name: Test WER
         type: wer
         value: 0.20626555409164105
       - name: Test CER
         type: cer
         value: 0.051648321634392154
---

<!-- 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. -->

#

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - SL dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2756
- Wer: 0.2279

## 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: 7.1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 100.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.3881        | 6.1   | 500  | 2.9710          | 1.0    |
| 2.6401        | 12.2  | 1000 | 1.7677          | 0.9734 |
| 1.5152        | 18.29 | 1500 | 0.5564          | 0.6011 |
| 1.2191        | 24.39 | 2000 | 0.4319          | 0.4390 |
| 1.0237        | 30.49 | 2500 | 0.3141          | 0.3175 |
| 0.8892        | 36.59 | 3000 | 0.2748          | 0.2689 |
| 0.8296        | 42.68 | 3500 | 0.2680          | 0.2534 |
| 0.7602        | 48.78 | 4000 | 0.2820          | 0.2506 |
| 0.7186        | 54.88 | 4500 | 0.2672          | 0.2398 |
| 0.6887        | 60.98 | 5000 | 0.2729          | 0.2402 |
| 0.6507        | 67.07 | 5500 | 0.2767          | 0.2361 |
| 0.6226        | 73.17 | 6000 | 0.2817          | 0.2332 |
| 0.6024        | 79.27 | 6500 | 0.2679          | 0.2279 |
| 0.5787        | 85.37 | 7000 | 0.2837          | 0.2316 |
| 0.5744        | 91.46 | 7500 | 0.2838          | 0.2284 |
| 0.5556        | 97.56 | 8000 | 0.2763          | 0.2281 |

### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0


---
language:
- hi
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- hi
- robust-speech-event
- model_for_talk
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-hi-cv8
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 8
      type: mozilla-foundation/common_voice_8_0
      args: hi
    metrics:
       - name: Test WER
         type: wer
         value: []
       - name: Test CER
         type: cer
         value: []
---

<!-- 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-300m-hi-cv8

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - HI  dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6510
- Wer: 0.3179

## 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:

- 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: 2000
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 12.5576       | 1.04  | 200  | 6.6594          | 1.0    |
| 4.4069        | 2.07  | 400  | 3.6011          | 1.0    |
| 3.4273        | 3.11  | 600  | 3.3370          | 1.0    |
| 2.1108        | 4.15  | 800  | 1.0641          | 0.6562 |
| 0.8817        | 5.18  | 1000 | 0.7178          | 0.5172 |
| 0.6508        | 6.22  | 1200 | 0.6612          | 0.4839 |
| 0.5524        | 7.25  | 1400 | 0.6458          | 0.4889 |
| 0.4992        | 8.29  | 1600 | 0.5791          | 0.4382 |
| 0.4669        | 9.33  | 1800 | 0.6039          | 0.4352 |
| 0.4441        | 10.36 | 2000 | 0.6276          | 0.4297 |
| 0.4172        | 11.4  | 2200 | 0.6183          | 0.4474 |
| 0.3872        | 12.44 | 2400 | 0.5886          | 0.4231 |
| 0.3692        | 13.47 | 2600 | 0.6448          | 0.4399 |
| 0.3385        | 14.51 | 2800 | 0.6344          | 0.4075 |
| 0.3246        | 15.54 | 3000 | 0.5896          | 0.4087 |
| 0.3026        | 16.58 | 3200 | 0.6158          | 0.4016 |
| 0.284         | 17.62 | 3400 | 0.6038          | 0.3906 |
| 0.2682        | 18.65 | 3600 | 0.6165          | 0.3900 |
| 0.2577        | 19.69 | 3800 | 0.5754          | 0.3805 |
| 0.2509        | 20.73 | 4000 | 0.6028          | 0.3925 |
| 0.2426        | 21.76 | 4200 | 0.6335          | 0.4138 |
| 0.2346        | 22.8  | 4400 | 0.6128          | 0.3870 |
| 0.2205        | 23.83 | 4600 | 0.6223          | 0.3831 |
| 0.2104        | 24.87 | 4800 | 0.6122          | 0.3781 |
| 0.1992        | 25.91 | 5000 | 0.6467          | 0.3792 |
| 0.1916        | 26.94 | 5200 | 0.6277          | 0.3636 |
| 0.1835        | 27.98 | 5400 | 0.6317          | 0.3773 |
| 0.1776        | 29.02 | 5600 | 0.6124          | 0.3614 |
| 0.1751        | 30.05 | 5800 | 0.6475          | 0.3628 |
| 0.1662        | 31.09 | 6000 | 0.6266          | 0.3504 |
| 0.1584        | 32.12 | 6200 | 0.6347          | 0.3532 |
| 0.1494        | 33.16 | 6400 | 0.6636          | 0.3491 |
| 0.1457        | 34.2  | 6600 | 0.6334          | 0.3507 |
| 0.1427        | 35.23 | 6800 | 0.6397          | 0.3442 |
| 0.1397        | 36.27 | 7000 | 0.6468          | 0.3496 |
| 0.1283        | 37.31 | 7200 | 0.6291          | 0.3416 |
| 0.1255        | 38.34 | 7400 | 0.6652          | 0.3461 |
| 0.1195        | 39.38 | 7600 | 0.6587          | 0.3342 |
| 0.1169        | 40.41 | 7800 | 0.6478          | 0.3319 |
| 0.1126        | 41.45 | 8000 | 0.6280          | 0.3291 |
| 0.1112        | 42.49 | 8200 | 0.6434          | 0.3290 |
| 0.1069        | 43.52 | 8400 | 0.6542          | 0.3268 |
| 0.1027        | 44.56 | 8600 | 0.6536          | 0.3239 |
| 0.0993        | 45.6  | 8800 | 0.6622          | 0.3257 |
| 0.0973        | 46.63 | 9000 | 0.6572          | 0.3192 |
| 0.0911        | 47.67 | 9200 | 0.6522          | 0.3175 |
| 0.0897        | 48.7  | 9400 | 0.6521          | 0.3200 |
| 0.0905        | 49.74 | 9600 | 0.6510          | 0.3179 |

### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0


---
language:
- br
license: apache-2.0
tags:
- generated_from_trainer
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_8_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-br-d10
  results:
  - task:
      type: automatic-speech-recognition
      name: Speech Recognition
    dataset:
      type: mozilla-foundation/common_voice_8_0
      name: Common Voice 8
      args: br
    metrics:
      - type: wer
        value: []
        name: Test WER
      - name: Test CER
        type: cer
        value: []
---

<!-- 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-300m-br-d10

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - BR dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1382
- Wer: 0.4895

## 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: 0.0004
- 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: 800
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 13.611        | 0.68  | 100  | 5.8492          | 1.0    |
| 3.8176        | 1.35  | 200  | 3.2181          | 1.0    |
| 3.0457        | 2.03  | 300  | 3.0902          | 1.0    |
| 2.2632        | 2.7   | 400  | 1.4882          | 0.9426 |
| 1.1965        | 3.38  | 500  | 1.1396          | 0.7950 |
| 0.984         | 4.05  | 600  | 1.0216          | 0.7583 |
| 0.8036        | 4.73  | 700  | 1.0258          | 0.7202 |
| 0.7061        | 5.41  | 800  | 0.9710          | 0.6820 |
| 0.689         | 6.08  | 900  | 0.9731          | 0.6488 |
| 0.6063        | 6.76  | 1000 | 0.9442          | 0.6569 |
| 0.5215        | 7.43  | 1100 | 1.0221          | 0.6671 |
| 0.4965        | 8.11  | 1200 | 0.9266          | 0.6181 |
| 0.4321        | 8.78  | 1300 | 0.9050          | 0.5991 |
| 0.3762        | 9.46  | 1400 | 0.9801          | 0.6134 |
| 0.3747        | 10.14 | 1500 | 0.9210          | 0.5747 |
| 0.3554        | 10.81 | 1600 | 0.9720          | 0.6051 |
| 0.3148        | 11.49 | 1700 | 0.9672          | 0.6099 |
| 0.3176        | 12.16 | 1800 | 1.0120          | 0.5966 |
| 0.2915        | 12.84 | 1900 | 0.9490          | 0.5653 |
| 0.2696        | 13.51 | 2000 | 0.9394          | 0.5819 |
| 0.2569        | 14.19 | 2100 | 1.0197          | 0.5667 |
| 0.2395        | 14.86 | 2200 | 0.9771          | 0.5608 |
| 0.2367        | 15.54 | 2300 | 1.0516          | 0.5678 |
| 0.2153        | 16.22 | 2400 | 1.0097          | 0.5679 |
| 0.2092        | 16.89 | 2500 | 1.0143          | 0.5430 |
| 0.2046        | 17.57 | 2600 | 1.0884          | 0.5631 |
| 0.1937        | 18.24 | 2700 | 1.0113          | 0.5648 |
| 0.1752        | 18.92 | 2800 | 1.0056          | 0.5470 |
| 0.164         | 19.59 | 2900 | 1.0340          | 0.5508 |
| 0.1723        | 20.27 | 3000 | 1.0743          | 0.5615 |
| 0.1535        | 20.95 | 3100 | 1.0495          | 0.5465 |
| 0.1432        | 21.62 | 3200 | 1.0390          | 0.5333 |
| 0.1561        | 22.3  | 3300 | 1.0798          | 0.5590 |
| 0.1384        | 22.97 | 3400 | 1.1716          | 0.5449 |
| 0.1359        | 23.65 | 3500 | 1.1154          | 0.5420 |
| 0.1356        | 24.32 | 3600 | 1.0883          | 0.5387 |
| 0.1355        | 25.0  | 3700 | 1.1114          | 0.5504 |
| 0.1158        | 25.68 | 3800 | 1.1171          | 0.5388 |
| 0.1166        | 26.35 | 3900 | 1.1335          | 0.5403 |
| 0.1165        | 27.03 | 4000 | 1.1374          | 0.5248 |
| 0.1064        | 27.7  | 4100 | 1.0336          | 0.5298 |
| 0.0987        | 28.38 | 4200 | 1.0407          | 0.5216 |
| 0.104         | 29.05 | 4300 | 1.1012          | 0.5350 |
| 0.0894        | 29.73 | 4400 | 1.1016          | 0.5310 |
| 0.0912        | 30.41 | 4500 | 1.1383          | 0.5302 |
| 0.0972        | 31.08 | 4600 | 1.0851          | 0.5214 |
| 0.0832        | 31.76 | 4700 | 1.1705          | 0.5311 |
| 0.0859        | 32.43 | 4800 | 1.0750          | 0.5192 |
| 0.0811        | 33.11 | 4900 | 1.0900          | 0.5180 |
| 0.0825        | 33.78 | 5000 | 1.1271          | 0.5196 |
| 0.07          | 34.46 | 5100 | 1.1289          | 0.5141 |
| 0.0689        | 35.14 | 5200 | 1.0960          | 0.5101 |
| 0.068         | 35.81 | 5300 | 1.1377          | 0.5050 |
| 0.0776        | 36.49 | 5400 | 1.0880          | 0.5194 |
| 0.0642        | 37.16 | 5500 | 1.1027          | 0.5076 |
| 0.0607        | 37.84 | 5600 | 1.1293          | 0.5119 |
| 0.0607        | 38.51 | 5700 | 1.1229          | 0.5103 |
| 0.0545        | 39.19 | 5800 | 1.1168          | 0.5103 |
| 0.0562        | 39.86 | 5900 | 1.1206          | 0.5073 |
| 0.0484        | 40.54 | 6000 | 1.1710          | 0.5019 |
| 0.0499        | 41.22 | 6100 | 1.1511          | 0.5100 |
| 0.0455        | 41.89 | 6200 | 1.1488          | 0.5009 |
| 0.0475        | 42.57 | 6300 | 1.1196          | 0.4944 |
| 0.0413        | 43.24 | 6400 | 1.1654          | 0.4996 |
| 0.0389        | 43.92 | 6500 | 1.0961          | 0.4930 |
| 0.0428        | 44.59 | 6600 | 1.0955          | 0.4938 |
| 0.039         | 45.27 | 6700 | 1.1323          | 0.4955 |
| 0.0352        | 45.95 | 6800 | 1.1040          | 0.4930 |
| 0.0334        | 46.62 | 6900 | 1.1382          | 0.4942 |
| 0.0338        | 47.3  | 7000 | 1.1264          | 0.4911 |
| 0.0307        | 47.97 | 7100 | 1.1216          | 0.4881 |
| 0.0286        | 48.65 | 7200 | 1.1459          | 0.4894 |
| 0.0348        | 49.32 | 7300 | 1.1419          | 0.4906 |
| 0.0329        | 50.0  | 7400 | 1.1382          | 0.4895 |

### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0


---
language:
- gn
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- gn
- robust-speech-event
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-gn-k1
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 8
      type: mozilla-foundation/common_voice_8_0
      args: gn
    metrics:
       - name: Test WER
         type: wer
         value: []
       - name: Test CER
         type: cer
         value: []
---

<!-- 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-300m-gn-k1

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - GN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9220
- Wer: 0.6631

## 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: 0.00018
- 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: 600
- num_epochs: 200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 15.9402       | 8.32   | 100  | 6.9185          | 1.0    |
| 4.6367        | 16.64  | 200  | 3.7416          | 1.0    |
| 3.4337        | 24.96  | 300  | 3.2581          | 1.0    |
| 3.2307        | 33.32  | 400  | 2.8008          | 1.0    |
| 1.3182        | 41.64  | 500  | 0.8359          | 0.8171 |
| 0.409         | 49.96  | 600  | 0.8470          | 0.8323 |
| 0.2573        | 58.32  | 700  | 0.7823          | 0.7576 |
| 0.1969        | 66.64  | 800  | 0.8306          | 0.7424 |
| 0.1469        | 74.96  | 900  | 0.9225          | 0.7713 |
| 0.1172        | 83.32  | 1000 | 0.7903          | 0.6951 |
| 0.1017        | 91.64  | 1100 | 0.8519          | 0.6921 |
| 0.0851        | 99.96  | 1200 | 0.8129          | 0.6646 |
| 0.071         | 108.32 | 1300 | 0.8614          | 0.7043 |
| 0.061         | 116.64 | 1400 | 0.8414          | 0.6921 |
| 0.0552        | 124.96 | 1500 | 0.8649          | 0.6905 |
| 0.0465        | 133.32 | 1600 | 0.8575          | 0.6646 |
| 0.0381        | 141.64 | 1700 | 0.8802          | 0.6723 |
| 0.0338        | 149.96 | 1800 | 0.8731          | 0.6845 |
| 0.0306        | 158.32 | 1900 | 0.9003          | 0.6585 |
| 0.0236        | 166.64 | 2000 | 0.9408          | 0.6616 |
| 0.021         | 174.96 | 2100 | 0.9353          | 0.6723 |
| 0.0212        | 183.32 | 2200 | 0.9269          | 0.6570 |
| 0.0191        | 191.64 | 2300 | 0.9277          | 0.6662 |
| 0.0161        | 199.96 | 2400 | 0.9220          | 0.6631 |

### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0


---
language:
- as
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- as
- robust-speech-event
- model_for_talk
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-as-with-LM-v1
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 8
      type: mozilla-foundation/common_voice_8_0
      args: hsb
    metrics:
       - name: Test WER
         type: wer
         value: []
       - name: Test CER
         type: cer
         value: []
---

<!-- 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-300m-as-g1

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - AS dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3327
- Wer: 0.5744

## 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: 1000
- num_epochs: 200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 14.1958       | 5.26   | 100  | 7.1919          | 1.0    |
| 5.0035        | 10.51  | 200  | 3.9362          | 1.0    |
| 3.6193        | 15.77  | 300  | 3.4451          | 1.0    |
| 3.4852        | 21.05  | 400  | 3.3536          | 1.0    |
| 2.8489        | 26.31  | 500  | 1.6451          | 0.9100 |
| 0.9568        | 31.56  | 600  | 1.0514          | 0.7561 |
| 0.4865        | 36.82  | 700  | 1.0434          | 0.7184 |
| 0.322         | 42.1   | 800  | 1.0825          | 0.7210 |
| 0.2383        | 47.36  | 900  | 1.1304          | 0.6897 |
| 0.2136        | 52.62  | 1000 | 1.1150          | 0.6854 |
| 0.179         | 57.87  | 1100 | 1.2453          | 0.6875 |
| 0.1539        | 63.15  | 1200 | 1.2211          | 0.6704 |
| 0.1303        | 68.41  | 1300 | 1.2859          | 0.6747 |
| 0.1183        | 73.67  | 1400 | 1.2775          | 0.6721 |
| 0.0994        | 78.92  | 1500 | 1.2321          | 0.6404 |
| 0.0991        | 84.21  | 1600 | 1.2766          | 0.6524 |
| 0.0887        | 89.46  | 1700 | 1.3026          | 0.6344 |
| 0.0754        | 94.72  | 1800 | 1.3199          | 0.6704 |
| 0.0693        | 99.97  | 1900 | 1.3044          | 0.6361 |
| 0.0568        | 105.26 | 2000 | 1.3541          | 0.6254 |
| 0.0536        | 110.51 | 2100 | 1.3320          | 0.6249 |
| 0.0529        | 115.77 | 2200 | 1.3370          | 0.6271 |
| 0.048         | 121.05 | 2300 | 1.2757          | 0.6031 |
| 0.0419        | 126.31 | 2400 | 1.2661          | 0.6172 |
| 0.0349        | 131.56 | 2500 | 1.2897          | 0.6048 |
| 0.0309        | 136.82 | 2600 | 1.2688          | 0.5962 |
| 0.0278        | 142.1  | 2700 | 1.2885          | 0.5954 |
| 0.0254        | 147.36 | 2800 | 1.2988          | 0.5915 |
| 0.0223        | 152.62 | 2900 | 1.3153          | 0.5941 |
| 0.0216        | 157.87 | 3000 | 1.2936          | 0.5937 |
| 0.0186        | 163.15 | 3100 | 1.2906          | 0.5877 |
| 0.0156        | 168.41 | 3200 | 1.3476          | 0.5962 |
| 0.0158        | 173.67 | 3300 | 1.3363          | 0.5847 |
| 0.0142        | 178.92 | 3400 | 1.3367          | 0.5847 |
| 0.0153        | 184.21 | 3500 | 1.3105          | 0.5757 |
| 0.0119        | 189.46 | 3600 | 1.3255          | 0.5705 |
| 0.0115        | 194.72 | 3700 | 1.3340          | 0.5787 |
| 0.0103        | 199.97 | 3800 | 1.3327          | 0.5744 |

### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0


---
language:
- mr
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- mr
- robust-speech-event
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-mr-with-LM-v1
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 8
      type: mozilla-foundation/common_voice_8_0
      args: mr
    metrics:
       - name: Test WER
         type: wer
         value: []
       - name: Test CER
         type: cer
         value: []
---

<!-- 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-300m-mr-v2

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - MR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8729
- Wer: 0.4942

## 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: 0.000333
- 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: 1000
- num_epochs: 200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 8.4934        | 9.09   | 200  | 3.7326          | 1.0    |
| 3.4234        | 18.18  | 400  | 3.3383          | 0.9996 |
| 3.2628        | 27.27  | 600  | 2.7482          | 0.9992 |
| 1.7743        | 36.36  | 800  | 0.6755          | 0.6787 |
| 1.0346        | 45.45  | 1000 | 0.6067          | 0.6193 |
| 0.8137        | 54.55  | 1200 | 0.6228          | 0.5612 |
| 0.6637        | 63.64  | 1400 | 0.5976          | 0.5495 |
| 0.5563        | 72.73  | 1600 | 0.7009          | 0.5383 |
| 0.4844        | 81.82  | 1800 | 0.6662          | 0.5287 |
| 0.4057        | 90.91  | 2000 | 0.6911          | 0.5303 |
| 0.3582        | 100.0  | 2200 | 0.7207          | 0.5327 |
| 0.3163        | 109.09 | 2400 | 0.7107          | 0.5118 |
| 0.2761        | 118.18 | 2600 | 0.7538          | 0.5118 |
| 0.2415        | 127.27 | 2800 | 0.7850          | 0.5178 |
| 0.2127        | 136.36 | 3000 | 0.8016          | 0.5034 |
| 0.1873        | 145.45 | 3200 | 0.8302          | 0.5187 |
| 0.1723        | 154.55 | 3400 | 0.9085          | 0.5223 |
| 0.1498        | 163.64 | 3600 | 0.8396          | 0.5126 |
| 0.1425        | 172.73 | 3800 | 0.8776          | 0.5094 |
| 0.1258        | 181.82 | 4000 | 0.8651          | 0.5014 |
| 0.117         | 190.91 | 4200 | 0.8772          | 0.4970 |
| 0.1093        | 200.0  | 4400 | 0.8729          | 0.4942 |

### Framework versions

- Transformers 4.16.1
- Pytorch 1.10.0+cu111
- Datasets 1.18.2
- Tokenizers 0.11.0


---
language:
- hsb
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- hsb
- robust-speech-event
- model_for_talk
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-hsb-v2
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 8
      type: mozilla-foundation/common_voice_8_0
      args: hsb
    metrics:
       - name: Test WER
         type: wer
         value: []
       - name: Test CER
         type: cer
         value: []
---

<!-- 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-300m-hsb-v2

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5328
- Wer: 0.4596

## 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: 0.00045
- 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: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 8.5979        | 3.23  | 100  | 3.5602          | 1.0    |
| 3.303         | 6.45  | 200  | 3.2238          | 1.0    |
| 3.2034        | 9.68  | 300  | 3.2002          | 0.9888 |
| 2.7986        | 12.9  | 400  | 1.2408          | 0.9210 |
| 1.3869        | 16.13 | 500  | 0.7973          | 0.7462 |
| 1.0228        | 19.35 | 600  | 0.6722          | 0.6788 |
| 0.8311        | 22.58 | 700  | 0.6100          | 0.6150 |
| 0.717         | 25.81 | 800  | 0.6236          | 0.6013 |
| 0.6264        | 29.03 | 900  | 0.6031          | 0.5575 |
| 0.5494        | 32.26 | 1000 | 0.5656          | 0.5309 |
| 0.4781        | 35.48 | 1100 | 0.5289          | 0.4996 |
| 0.4311        | 38.71 | 1200 | 0.5375          | 0.4768 |
| 0.3902        | 41.94 | 1300 | 0.5246          | 0.4703 |
| 0.3508        | 45.16 | 1400 | 0.5382          | 0.4696 |
| 0.3199        | 48.39 | 1500 | 0.5328          | 0.4596 |

### Framework versions

- Transformers 4.16.1
- Pytorch 1.10.0+cu111
- Datasets 1.18.2
- Tokenizers 0.11.0


---
language:
- ab
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_7_0
- generated_from_trainer
- ab
- robust-speech-event
- model_for_talk
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-ab-CV7
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 7
      type: mozilla-foundation/common_voice_7_0
      args: ab
    metrics:
       - name: Test WER
         type: wer
         value: 0.5291160452450775
       - name: Test CER
         type: cer
         value: 0.10630270750110964
---

<!-- 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. -->

#

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - AB dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5620
- Wer: 0.5651

## 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: 7.5e-05
- 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: 2000
- num_epochs: 100.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 9.6445        | 13.64 | 300  | 4.3963          | 1.0    |
| 3.6459        | 27.27 | 600  | 3.2267          | 1.0    |
| 3.0978        | 40.91 | 900  | 3.0927          | 1.0    |
| 2.8357        | 54.55 | 1200 | 2.1462          | 1.0029 |
| 1.2723        | 68.18 | 1500 | 0.6747          | 0.6996 |
| 0.6528        | 81.82 | 1800 | 0.5928          | 0.6422 |
| 0.4905        | 95.45 | 2100 | 0.5587          | 0.5681 |

### Framework versions

- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0

### Evaluation Script

Evaluation script for evaluating the performance of the fine-tuned model on Mozilla-foundation/common_voice_7_0 with split test

!python eval.py \
    --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-ab-v16 \
    --dataset mozilla-foundation/common_voice_7_0 --config ab --split test --log_outputs


---
language:
- bg
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- bg
- robust-speech-event
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-bg-with-LM-v1
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 8
      type: mozilla-foundation/common_voice_8_0
      args: bg
    metrics:
       - name: Test WER
         type: wer
         value: []
       - name: Test CER
         type: cer
         value: []
---

<!-- 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-300m-bg-d2

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - BG dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3421
- Wer: 0.2860

## 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: 0.00025
- 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: 700
- num_epochs: 35
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 6.8791        | 1.74  | 200  | 3.1902          | 1.0    |
| 3.0441        | 3.48  | 400  | 2.8098          | 0.9864 |
| 1.1499        | 5.22  | 600  | 0.4668          | 0.5014 |
| 0.4968        | 6.96  | 800  | 0.4162          | 0.4472 |
| 0.3553        | 8.7   | 1000 | 0.3580          | 0.3777 |
| 0.3027        | 10.43 | 1200 | 0.3422          | 0.3506 |
| 0.2562        | 12.17 | 1400 | 0.3556          | 0.3639 |
| 0.2272        | 13.91 | 1600 | 0.3621          | 0.3583 |
| 0.2125        | 15.65 | 1800 | 0.3436          | 0.3358 |
| 0.1904        | 17.39 | 2000 | 0.3650          | 0.3545 |
| 0.1695        | 19.13 | 2200 | 0.3366          | 0.3241 |
| 0.1532        | 20.87 | 2400 | 0.3550          | 0.3311 |
| 0.1453        | 22.61 | 2600 | 0.3582          | 0.3131 |
| 0.1359        | 24.35 | 2800 | 0.3524          | 0.3084 |
| 0.1233        | 26.09 | 3000 | 0.3503          | 0.2973 |
| 0.1114        | 27.83 | 3200 | 0.3434          | 0.2946 |
| 0.1051        | 29.57 | 3400 | 0.3474          | 0.2956 |
| 0.0965        | 31.3  | 3600 | 0.3426          | 0.2907 |
| 0.0923        | 33.04 | 3800 | 0.3478          | 0.2894 |
| 0.0894        | 34.78 | 4000 | 0.3421          | 0.2860 |

### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0


---
language:
- mr
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- mr
- robust-speech-event
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-mr-v2
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 8
      type: mozilla-foundation/common_voice_8_0
      args: mr
    metrics:
       - name: Test WER
         type: wer
         value: []
       - name: Test CER
         type: cer
         value: []
---

<!-- 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-300m-mr-v2

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - MR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8729
- Wer: 0.4942

## 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: 0.000333
- 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: 1000
- num_epochs: 200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 8.4934        | 9.09   | 200  | 3.7326          | 1.0    |
| 3.4234        | 18.18  | 400  | 3.3383          | 0.9996 |
| 3.2628        | 27.27  | 600  | 2.7482          | 0.9992 |
| 1.7743        | 36.36  | 800  | 0.6755          | 0.6787 |
| 1.0346        | 45.45  | 1000 | 0.6067          | 0.6193 |
| 0.8137        | 54.55  | 1200 | 0.6228          | 0.5612 |
| 0.6637        | 63.64  | 1400 | 0.5976          | 0.5495 |
| 0.5563        | 72.73  | 1600 | 0.7009          | 0.5383 |
| 0.4844        | 81.82  | 1800 | 0.6662          | 0.5287 |
| 0.4057        | 90.91  | 2000 | 0.6911          | 0.5303 |
| 0.3582        | 100.0  | 2200 | 0.7207          | 0.5327 |
| 0.3163        | 109.09 | 2400 | 0.7107          | 0.5118 |
| 0.2761        | 118.18 | 2600 | 0.7538          | 0.5118 |
| 0.2415        | 127.27 | 2800 | 0.7850          | 0.5178 |
| 0.2127        | 136.36 | 3000 | 0.8016          | 0.5034 |
| 0.1873        | 145.45 | 3200 | 0.8302          | 0.5187 |
| 0.1723        | 154.55 | 3400 | 0.9085          | 0.5223 |
| 0.1498        | 163.64 | 3600 | 0.8396          | 0.5126 |
| 0.1425        | 172.73 | 3800 | 0.8776          | 0.5094 |
| 0.1258        | 181.82 | 4000 | 0.8651          | 0.5014 |
| 0.117         | 190.91 | 4200 | 0.8772          | 0.4970 |
| 0.1093        | 200.0  | 4400 | 0.8729          | 0.4942 |

### Framework versions

- Transformers 4.16.1
- Pytorch 1.10.0+cu111
- Datasets 1.18.2
- Tokenizers 0.11.0


---
language:
- sl
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- sl
- robust-speech-event
- model_for_talk
datasets:
- common_voice
model-index:
- name: wav2vec2-xls-r-sl-a2
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 8
      type: mozilla-foundation/common_voice_8_0
      args: sl
    metrics:
       - name: Test WER
         type: wer
         value: 0.21695212999560826
       - name: Test CER
         type: cer
         value: 0.052850080572474256
---

<!-- 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. -->

#

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - SL dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2855
- Wer: 0.2401

## 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: 7e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 100.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 6.9294        | 6.1   | 500  | 2.9712          | 1.0    |
| 2.8305        | 12.2  | 1000 | 1.7073          | 0.9479 |
| 1.4795        | 18.29 | 1500 | 0.5756          | 0.6397 |
| 1.3433        | 24.39 | 2000 | 0.4968          | 0.5424 |
| 1.1766        | 30.49 | 2500 | 0.4185          | 0.4743 |
| 1.0017        | 36.59 | 3000 | 0.3303          | 0.3578 |
| 0.9358        | 42.68 | 3500 | 0.3003          | 0.3051 |
| 0.8358        | 48.78 | 4000 | 0.3045          | 0.2884 |
| 0.7647        | 54.88 | 4500 | 0.2866          | 0.2677 |
| 0.7482        | 60.98 | 5000 | 0.2829          | 0.2585 |
| 0.6943        | 67.07 | 5500 | 0.2782          | 0.2478 |
| 0.6586        | 73.17 | 6000 | 0.2911          | 0.2537 |
| 0.6425        | 79.27 | 6500 | 0.2817          | 0.2462 |
| 0.6067        | 85.37 | 7000 | 0.2910          | 0.2436 |
| 0.5974        | 91.46 | 7500 | 0.2875          | 0.2430 |
| 0.5812        | 97.56 | 8000 | 0.2852          | 0.2396 |

### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0


---
language:
- as
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- as
- robust-speech-event
- model_for_talk
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-as-g1
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 8
      type: mozilla-foundation/common_voice_8_0
      args: hsb
    metrics:
       - name: Test WER
         type: wer
         value: []
       - name: Test CER
         type: cer
         value: []
---

<!-- 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-300m-as-g1

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - AS dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3327
- Wer: 0.5744

## 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: 1000
- num_epochs: 200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 14.1958       | 5.26   | 100  | 7.1919          | 1.0    |
| 5.0035        | 10.51  | 200  | 3.9362          | 1.0    |
| 3.6193        | 15.77  | 300  | 3.4451          | 1.0    |
| 3.4852        | 21.05  | 400  | 3.3536          | 1.0    |
| 2.8489        | 26.31  | 500  | 1.6451          | 0.9100 |
| 0.9568        | 31.56  | 600  | 1.0514          | 0.7561 |
| 0.4865        | 36.82  | 700  | 1.0434          | 0.7184 |
| 0.322         | 42.1   | 800  | 1.0825          | 0.7210 |
| 0.2383        | 47.36  | 900  | 1.1304          | 0.6897 |
| 0.2136        | 52.62  | 1000 | 1.1150          | 0.6854 |
| 0.179         | 57.87  | 1100 | 1.2453          | 0.6875 |
| 0.1539        | 63.15  | 1200 | 1.2211          | 0.6704 |
| 0.1303        | 68.41  | 1300 | 1.2859          | 0.6747 |
| 0.1183        | 73.67  | 1400 | 1.2775          | 0.6721 |
| 0.0994        | 78.92  | 1500 | 1.2321          | 0.6404 |
| 0.0991        | 84.21  | 1600 | 1.2766          | 0.6524 |
| 0.0887        | 89.46  | 1700 | 1.3026          | 0.6344 |
| 0.0754        | 94.72  | 1800 | 1.3199          | 0.6704 |
| 0.0693        | 99.97  | 1900 | 1.3044          | 0.6361 |
| 0.0568        | 105.26 | 2000 | 1.3541          | 0.6254 |
| 0.0536        | 110.51 | 2100 | 1.3320          | 0.6249 |
| 0.0529        | 115.77 | 2200 | 1.3370          | 0.6271 |
| 0.048         | 121.05 | 2300 | 1.2757          | 0.6031 |
| 0.0419        | 126.31 | 2400 | 1.2661          | 0.6172 |
| 0.0349        | 131.56 | 2500 | 1.2897          | 0.6048 |
| 0.0309        | 136.82 | 2600 | 1.2688          | 0.5962 |
| 0.0278        | 142.1  | 2700 | 1.2885          | 0.5954 |
| 0.0254        | 147.36 | 2800 | 1.2988          | 0.5915 |
| 0.0223        | 152.62 | 2900 | 1.3153          | 0.5941 |
| 0.0216        | 157.87 | 3000 | 1.2936          | 0.5937 |
| 0.0186        | 163.15 | 3100 | 1.2906          | 0.5877 |
| 0.0156        | 168.41 | 3200 | 1.3476          | 0.5962 |
| 0.0158        | 173.67 | 3300 | 1.3363          | 0.5847 |
| 0.0142        | 178.92 | 3400 | 1.3367          | 0.5847 |
| 0.0153        | 184.21 | 3500 | 1.3105          | 0.5757 |
| 0.0119        | 189.46 | 3600 | 1.3255          | 0.5705 |
| 0.0115        | 194.72 | 3700 | 1.3340          | 0.5787 |
| 0.0103        | 199.97 | 3800 | 1.3327          | 0.5744 |

### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0


---
language:
- rm-sursilv
license: apache-2.0
tags:
- automatic-speech-recognition
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_8_0
metrics:
- wer
model-index:
- name: wav2vec2-xls-r-300m-rm-sursilv-d11
  results:
  - task:
      type: automatic-speech-recognition
      name: Speech Recognition
    dataset:
      type: mozilla-foundation/common_voice_8_0
      name: Common Voice 8
      args: rm-sursilv
    metrics:
      - type: wer
        value: []
        name: Test WER
      - name: Test CER
        type: cer
        value: []
---

<!-- 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. -->

#

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - RM-SURSILV dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2511
- Wer: 0.2415

## 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: 7e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 125.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer    |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 2.3958        | 17.44  | 1500  | 0.6808          | 0.6521 |
| 0.9663        | 34.88  | 3000  | 0.3023          | 0.3718 |
| 0.7963        | 52.33  | 4500  | 0.2588          | 0.3046 |
| 0.6893        | 69.77  | 6000  | 0.2436          | 0.2718 |
| 0.6148        | 87.21  | 7500  | 0.2521          | 0.2572 |
| 0.5556        | 104.65 | 9000  | 0.2490          | 0.2442 |
| 0.5258        | 122.09 | 10500 | 0.2515          | 0.2442 |

### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0


---
language:
- or
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- or
- robust-speech-event
- model_for_talk
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-or-with-LM
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 8
      type: mozilla-foundation/common_voice_8_0
      args: or
    metrics:
       - name: Test WER
         type: wer
         value: []
       - name: Test CER
         type: cer
         value: []
---

<!-- 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-300m-or-with-LM

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - OR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9571
- Wer: 0.5450

## 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: 0.000111
- 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: 800
- num_epochs: 200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 9.2958        | 12.5  | 300  | 4.9014          | 1.0    |
| 3.4065        | 25.0  | 600  | 3.5150          | 1.0    |
| 1.5402        | 37.5  | 900  | 0.8356          | 0.7249 |
| 0.6049        | 50.0  | 1200 | 0.7754          | 0.6349 |
| 0.4074        | 62.5  | 1500 | 0.7994          | 0.6217 |
| 0.3097        | 75.0  | 1800 | 0.8815          | 0.5985 |
| 0.2593        | 87.5  | 2100 | 0.8532          | 0.5754 |
| 0.2097        | 100.0 | 2400 | 0.9077          | 0.5648 |
| 0.1784        | 112.5 | 2700 | 0.9047          | 0.5668 |
| 0.1567        | 125.0 | 3000 | 0.9019          | 0.5728 |
| 0.1315        | 137.5 | 3300 | 0.9295          | 0.5827 |
| 0.1125        | 150.0 | 3600 | 0.9256          | 0.5681 |
| 0.1035        | 162.5 | 3900 | 0.9148          | 0.5496 |
| 0.0901        | 175.0 | 4200 | 0.9480          | 0.5483 |
| 0.0817        | 187.5 | 4500 | 0.9799          | 0.5516 |
| 0.079         | 200.0 | 4800 | 0.9571          | 0.5450 |

### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0


---
language:
- sr
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- sr
- robust-speech-event
- model_for_talk
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-sr-v20
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 8
      type: mozilla-foundation/common_voice_8_0
      args: sr
    metrics:
       - name: Test WER
         type: wer
         value: []
       - name: Test CER
         type: cer
         value: []
---

<!-- 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-300m-sr-v20

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - SR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6695
- Wer: 0.3355

## 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: 800
- num_epochs: 200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 8.2198        | 7.5   | 300  | 2.9960          | 1.0    |
| 2.0533        | 15.0  | 600  | 0.6508          | 0.6314 |
| 0.4176        | 22.5  | 900  | 0.5726          | 0.5170 |
| 0.2327        | 30.0  | 1200 | 0.5771          | 0.5296 |
| 0.1723        | 37.5  | 1500 | 0.5508          | 0.4377 |
| 0.1226        | 45.0  | 1800 | 0.6567          | 0.4363 |
| 0.1101        | 52.5  | 2100 | 0.5819          | 0.4452 |
| 0.0934        | 60.0  | 2400 | 0.6449          | 0.4354 |
| 0.0752        | 67.5  | 2700 | 0.5584          | 0.4162 |
| 0.0645        | 75.0  | 3000 | 0.6289          | 0.4162 |
| 0.0539        | 82.5  | 3300 | 0.6153          | 0.4232 |
| 0.0482        | 90.0  | 3600 | 0.6772          | 0.4811 |
| 0.0441        | 97.5  | 3900 | 0.6156          | 0.4582 |
| 0.0403        | 105.0 | 4200 | 0.6077          | 0.3971 |
| 0.0371        | 112.5 | 4500 | 0.7354          | 0.4148 |
| 0.0279        | 120.0 | 4800 | 0.6316          | 0.3598 |
| 0.0198        | 127.5 | 5100 | 0.6615          | 0.3626 |
| 0.0185        | 135.0 | 5400 | 0.6914          | 0.3658 |
| 0.0183        | 142.5 | 5700 | 0.7087          | 0.3742 |
| 0.0154        | 150.0 | 6000 | 0.6930          | 0.3542 |
| 0.0143        | 157.5 | 6300 | 0.6787          | 0.3383 |
| 0.0118        | 165.0 | 6600 | 0.6347          | 0.3476 |
| 0.0101        | 172.5 | 6900 | 0.6235          | 0.3434 |
| 0.0103        | 180.0 | 7200 | 0.6078          | 0.3434 |
| 0.0063        | 187.5 | 7500 | 0.6740          | 0.3411 |
| 0.0057        | 195.0 | 7800 | 0.6695          | 0.3355 |

### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0


---
language:
- myv
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- myv
- robust-speech-event
- model_for_talk
datasets:
- common_voice
model-index:
- name: wav2vec2-xls-r-myv-a1
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 8
      type: mozilla-foundation/common_voice_8_0
      args: myv
    metrics:
       - name: Test WER
         type: wer
         value: []
       - name: Test CER
         type: cer
         value: []
---

<!-- 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. -->

#

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - MYV dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0356
- Wer: 0.6524

## 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: 0.0004
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 800
- num_epochs: 200.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer    |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 5.649         | 9.62   | 500   | 3.0038          | 1.0    |
| 1.6272        | 19.23  | 1000  | 0.7362          | 0.7819 |
| 1.1354        | 28.85  | 1500  | 0.6410          | 0.7111 |
| 1.0424        | 38.46  | 2000  | 0.6907          | 0.7431 |
| 0.9293        | 48.08  | 2500  | 0.7249          | 0.7102 |
| 0.8246        | 57.69  | 3000  | 0.7422          | 0.6966 |
| 0.7837        | 67.31  | 3500  | 0.7413          | 0.6813 |
| 0.7147        | 76.92  | 4000  | 0.7873          | 0.6930 |
| 0.6276        | 86.54  | 4500  | 0.8038          | 0.6677 |
| 0.6041        | 96.15  | 5000  | 0.8240          | 0.6831 |
| 0.5336        | 105.77 | 5500  | 0.8748          | 0.6749 |
| 0.4705        | 115.38 | 6000  | 0.9006          | 0.6497 |
| 0.43          | 125.0  | 6500  | 0.8954          | 0.6551 |
| 0.3859        | 134.62 | 7000  | 0.9074          | 0.6614 |
| 0.3342        | 144.23 | 7500  | 0.9693          | 0.6560 |
| 0.3155        | 153.85 | 8000  | 1.0073          | 0.6691 |
| 0.2673        | 163.46 | 8500  | 1.0170          | 0.6632 |
| 0.2409        | 173.08 | 9000  | 1.0304          | 0.6709 |
| 0.2189        | 182.69 | 9500  | 0.9965          | 0.6546 |
| 0.1973        | 192.31 | 10000 | 1.0360          | 0.6551 |

### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0

### Evaluation Script

!python eval.py \
    --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-myv-v1 \
    --dataset mozilla-foundation/common_voice_8_0 --config myv --split test --log_outputs


---
language:
- sl
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- sl
- robust-speech-event
- model_for_talk
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-sl-with-LM-v2
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 8
      type: mozilla-foundation/common_voice_8_0
      args: sl
    metrics:
       - name: Test WER
         type: wer
         value: 0.21695212999560826
       - name: Test CER
         type: cer
         value: 0.052850080572474256
---

<!-- 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. -->

#

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - SL dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2855
- Wer: 0.2401

## 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: 7e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 100.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 6.9294        | 6.1   | 500  | 2.9712          | 1.0    |
| 2.8305        | 12.2  | 1000 | 1.7073          | 0.9479 |
| 1.4795        | 18.29 | 1500 | 0.5756          | 0.6397 |
| 1.3433        | 24.39 | 2000 | 0.4968          | 0.5424 |
| 1.1766        | 30.49 | 2500 | 0.4185          | 0.4743 |
| 1.0017        | 36.59 | 3000 | 0.3303          | 0.3578 |
| 0.9358        | 42.68 | 3500 | 0.3003          | 0.3051 |
| 0.8358        | 48.78 | 4000 | 0.3045          | 0.2884 |
| 0.7647        | 54.88 | 4500 | 0.2866          | 0.2677 |
| 0.7482        | 60.98 | 5000 | 0.2829          | 0.2585 |
| 0.6943        | 67.07 | 5500 | 0.2782          | 0.2478 |
| 0.6586        | 73.17 | 6000 | 0.2911          | 0.2537 |
| 0.6425        | 79.27 | 6500 | 0.2817          | 0.2462 |
| 0.6067        | 85.37 | 7000 | 0.2910          | 0.2436 |
| 0.5974        | 91.46 | 7500 | 0.2875          | 0.2430 |
| 0.5812        | 97.56 | 8000 | 0.2852          | 0.2396 |

### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0