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# wav2vec2-large-xls-r-300m-sat-a3

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: 0.8961
- Wer: 0.3976

### 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-sat-a3 --dataset mozilla-foundation/common_voice_8_0 --config sat --split test --log_outputs

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

Note: Santali (Ol Chiki) language not found in speech-recognition-community-v2/dev_data


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

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 11.1266       | 33.29  | 100  | 2.8577          | 1.0    |
| 2.1549        | 66.57  | 200  | 1.0799          | 0.5542 |
| 0.5628        | 99.86  | 300  | 0.7973          | 0.4016 |
| 0.0779        | 133.29 | 400  | 0.8424          | 0.4177 |
| 0.0404        | 166.57 | 500  | 0.9048          | 0.4137 |
| 0.0212        | 199.86 | 600  | 0.8961          | 0.3976 |


### 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", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-sat-a3", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Common Voice 8", "type": "mozilla-foundation/common_voice_8_0", "args": "sat"}, "metrics": [{"type": "wer", "value": 0.357429718875502, "name": "Test WER"}, {"type": "cer", "value": 0.14203730272596843, "name": "Test CER"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Robust Speech Event - Dev Data", "type": "speech-recognition-community-v2/dev_data", "args": "sat"}, "metrics": [{"type": "wer", "value": "NA", "name": "Test WER"}, {"type": "cer", "value": "NA", "name": "Test CER"}]}]}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition mozilla-foundation/common_voice_8_0 generated_from_trainer sat 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 #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #sat #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 

wav2vec2-large-xls-r-300m-sat-a3
================================


This model is a fine-tuned version of 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: 0.8961
* Wer: 0.3976


### 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-sat-a3 --dataset mozilla-foundation/common\_voice\_8\_0 --config sat --split test --log\_outputs


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


Note: Santali (Ol Chiki) language not found in speech-recognition-community-v2/dev\_data


### 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: 200
* num\_epochs: 200
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


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



### 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-sat-a3 --dataset mozilla-foundation/common\_voice\_8\_0 --config sat --split test --log\_outputs


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


Note: Santali (Ol Chiki) language not found in speech-recognition-community-v2/dev\_data ### 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: 200
* num\_epochs: 200
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.16.2
* Pytorch 1.10.0+cu111
* Datasets 1.18.3
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #sat #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 
 ### 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-sat-a3 --dataset mozilla-foundation/common\_voice\_8\_0 --config sat --split test --log\_outputs


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


Note: Santali (Ol Chiki) language not found in speech-recognition-community-v2/dev\_data ### 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: 200
* num\_epochs: 200
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.16.2
* Pytorch 1.10.0+cu111
* Datasets 1.18.3
* Tokenizers 0.11.0
passage: TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #sat #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 
### 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-sat-a3 --dataset mozilla-foundation/common\_voice\_8\_0 --config sat --split test --log\_outputs


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


Note: Santali (Ol Chiki) language not found in speech-recognition-community-v2/dev\_data### 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: 200
* num\_epochs: 200
* mixed\_precision\_training: Native AMP### Training results### Framework versions


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