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# 

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 - KK dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7149
- Wer: 0.451

# Evaluation Commands

1. To evaluate on mozilla-foundation/common_voice_8_0 with test split

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

2. To evaluate on speech-recognition-community-v2/dev_data

Kazakh language isn't available in speech-recognition-community-v2/dev_data

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.000222
- 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: 150.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 9.6799        | 9.09   | 200  | 3.6119          | 1.0    |
| 3.1332        | 18.18  | 400  | 2.5352          | 1.005  |
| 1.0465        | 27.27  | 600  | 0.6169          | 0.682  |
| 0.3452        | 36.36  | 800  | 0.6572          | 0.607  |
| 0.2575        | 45.44  | 1000 | 0.6527          | 0.578  |
| 0.2088        | 54.53  | 1200 | 0.6828          | 0.551  |
| 0.158         | 63.62  | 1400 | 0.7074          | 0.5575 |
| 0.1309        | 72.71  | 1600 | 0.6523          | 0.5595 |
| 0.1074        | 81.8   | 1800 | 0.7262          | 0.5415 |
| 0.087         | 90.89  | 2000 | 0.7199          | 0.521  |
| 0.0711        | 99.98  | 2200 | 0.7113          | 0.523  |
| 0.0601        | 109.09 | 2400 | 0.6863          | 0.496  |
| 0.0451        | 118.18 | 2600 | 0.6998          | 0.483  |
| 0.0378        | 127.27 | 2800 | 0.6971          | 0.4615 |
| 0.0319        | 136.36 | 3000 | 0.7119          | 0.4475 |
| 0.0305        | 145.44 | 3200 | 0.7181          | 0.459  |


### Framework versions

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

### Evaluation Command

!python eval.py \
    --model_id DrishtiSharma/wav2vec2-xls-r-300m-kk-n2 \
    --dataset mozilla-foundation/common_voice_8_0 --config kk --split test --log_outputs
{"language": ["kk"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "kk", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-kk-with-LM", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Common Voice 8", "type": "mozilla-foundation/common_voice_8_0", "args": "ru"}, "metrics": [{"type": "wer", "value": 0.4355, "name": "Test WER"}, {"type": "cer", "value": 0.10469915859660263, "name": "Test CER"}, {"type": "wer", "value": 0.417, "name": "Test WER (+LM)"}, {"type": "cer", "value": 0.10319098269566598, "name": "Test CER (+LM)"}, {"type": "wer", "value": 41.7, "name": "Test WER"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Robust Speech Event - Dev Data", "type": "speech-recognition-community-v2/dev_data", "args": "kk"}, "metrics": [{"type": "wer", "value": "NA", "name": "Test WER"}, {"type": "cer", "value": "NA", "name": "Test CER"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Robust Speech Event - Test Data", "type": "speech-recognition-community-v2/eval_data", "args": "kk"}, "metrics": [{"type": "wer", "value": 67.09, "name": "Test WER"}]}]}]}
transformers pytorch wav2vec2 automatic-speech-recognition mozilla-foundation/common_voice_8_0 generated_from_trainer kk robust-speech-event model_for_talk hf-asr-leaderboard dataset:mozilla-foundation/common_voice_8_0 license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #kk #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 


This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - KK dataset.
It achieves the following results on the evaluation set:


* Loss: 0.7149
* Wer: 0.451


Evaluation Commands
===================


1. To evaluate on mozilla-foundation/common\_voice\_8\_0 with test split


python URL --model\_id DrishtiSharma/wav2vec2-large-xls-r-300m-kk-with-LM --dataset mozilla-foundation/common\_voice\_8\_0 --config kk --split test --log\_outputs


2. To evaluate on speech-recognition-community-v2/dev\_data


Kazakh language isn't available in speech-recognition-community-v2/dev\_data


### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.000222
* 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: 150.0
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


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


### Evaluation Command


!python URL   

--model\_id DrishtiSharma/wav2vec2-xls-r-300m-kk-n2   

--dataset mozilla-foundation/common\_voice\_8\_0 --config kk --split test --log\_outputs



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.000222
* 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: 150.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.2.dev0
* Tokenizers 0.11.0 ### Evaluation Command


!python URL   

--model\_id DrishtiSharma/wav2vec2-xls-r-300m-kk-n2   

--dataset mozilla-foundation/common\_voice\_8\_0 --config kk --split test --log\_outputs
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #kk #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.000222
* 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: 150.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.2.dev0
* Tokenizers 0.11.0 ### Evaluation Command


!python URL   

--model\_id DrishtiSharma/wav2vec2-xls-r-300m-kk-n2   

--dataset mozilla-foundation/common\_voice\_8\_0 --config kk --split test --log\_outputs
passage: TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #kk #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.000222
* 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: 150.0
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.2.dev0
* Tokenizers 0.11.0### Evaluation Command


!python URL   

--model\_id DrishtiSharma/wav2vec2-xls-r-300m-kk-n2   

--dataset mozilla-foundation/common\_voice\_8\_0 --config kk --split test --log\_outputs