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# 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

### 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-mr-v2 --dataset mozilla-foundation/common_voice_8_0 --config mr --split test --log_outputs

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

python eval.py --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-mr-v2 --dataset speech-recognition-community-v2/dev_data --config mr --split validation --chunk_length_s 10 --stride_length_s 1

Note: Marathi language not found in speech-recognition-community-v2/dev_data!

### 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": ["mr"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "mr", "robust-speech-event", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-mr-v2", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Common Voice 8", "type": "mozilla-foundation/common_voice_8_0", "args": "mr"}, "metrics": [{"type": "wer", "value": 0.49378259125551544, "name": "Test WER"}, {"type": "cer", "value": 0.12470799640610962, "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": "mr"}, "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 mr robust-speech-event 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 #mr #robust-speech-event #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-mr-v2
===============================


This model is a fine-tuned version of 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


### 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-mr-v2 --dataset mozilla-foundation/common\_voice\_8\_0 --config mr --split test --log\_outputs


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


python URL --model\_id DrishtiSharma/wav2vec2-large-xls-r-300m-mr-v2 --dataset speech-recognition-community-v2/dev\_data --config mr --split validation --chunk\_length\_s 10 --stride\_length\_s 1


Note: Marathi language not found in speech-recognition-community-v2/dev\_data!


### 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



### Framework versions


* Transformers 4.16.1
* Pytorch 1.10.0+cu111
* Datasets 1.18.2
* 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-mr-v2 --dataset mozilla-foundation/common\_voice\_8\_0 --config mr --split test --log\_outputs


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


python URL --model\_id DrishtiSharma/wav2vec2-large-xls-r-300m-mr-v2 --dataset speech-recognition-community-v2/dev\_data --config mr --split validation --chunk\_length\_s 10 --stride\_length\_s 1


Note: Marathi language not found in speech-recognition-community-v2/dev\_data! ### 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 ### Framework versions


* Transformers 4.16.1
* Pytorch 1.10.0+cu111
* Datasets 1.18.2
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #mr #robust-speech-event #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-mr-v2 --dataset mozilla-foundation/common\_voice\_8\_0 --config mr --split test --log\_outputs


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


python URL --model\_id DrishtiSharma/wav2vec2-large-xls-r-300m-mr-v2 --dataset speech-recognition-community-v2/dev\_data --config mr --split validation --chunk\_length\_s 10 --stride\_length\_s 1


Note: Marathi language not found in speech-recognition-community-v2/dev\_data! ### 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 ### Framework versions


* Transformers 4.16.1
* Pytorch 1.10.0+cu111
* Datasets 1.18.2
* Tokenizers 0.11.0
passage: TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #mr #robust-speech-event #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-mr-v2 --dataset mozilla-foundation/common\_voice\_8\_0 --config mr --split test --log\_outputs


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


python URL --model\_id DrishtiSharma/wav2vec2-large-xls-r-300m-mr-v2 --dataset speech-recognition-community-v2/dev\_data --config mr --split validation --chunk\_length\_s 10 --stride\_length\_s 1


Note: Marathi language not found in speech-recognition-community-v2/dev\_data!### 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