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# wav2vec2-large-xls-r-300m-bas-v1

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 - BAS dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5997
- Wer: 0.3870

### 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-bas-v1 --dataset mozilla-foundation/common_voice_8_0 --config bas --split test --log_outputs

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

Basaa (bas) language isn't available in speech-recognition-community-v2/dev_data

### 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: 500
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 12.7076       | 5.26  | 200  | 3.6361          | 1.0    |
| 3.1657        | 10.52 | 400  | 3.0101          | 1.0    |
| 2.3987        | 15.78 | 600  | 0.9125          | 0.6774 |
| 1.0079        | 21.05 | 800  | 0.6477          | 0.5352 |
| 0.7392        | 26.31 | 1000 | 0.5432          | 0.4929 |
| 0.6114        | 31.57 | 1200 | 0.5498          | 0.4639 |
| 0.5222        | 36.83 | 1400 | 0.5220          | 0.4561 |
| 0.4648        | 42.1  | 1600 | 0.5586          | 0.4289 |
| 0.4103        | 47.36 | 1800 | 0.5337          | 0.4082 |
| 0.3692        | 52.62 | 2000 | 0.5421          | 0.3861 |
| 0.3403        | 57.88 | 2200 | 0.5549          | 0.4096 |
| 0.3011        | 63.16 | 2400 | 0.5833          | 0.3925 |
| 0.2932        | 68.42 | 2600 | 0.5674          | 0.3815 |
| 0.2696        | 73.68 | 2800 | 0.5734          | 0.3889 |
| 0.2496        | 78.94 | 3000 | 0.5968          | 0.3985 |
| 0.2289        | 84.21 | 3200 | 0.5888          | 0.3893 |
| 0.2091        | 89.47 | 3400 | 0.5849          | 0.3852 |
| 0.2005        | 94.73 | 3600 | 0.5938          | 0.3875 |
| 0.1876        | 99.99 | 3800 | 0.5997          | 0.3870 |


### Framework versions

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

{"language": ["bas"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "bas", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-bas-v1", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Common Voice 8", "type": "mozilla-foundation/common_voice_8_0", "args": "bas"}, "metrics": [{"type": "wer", "value": 0.3566497929130234, "name": "Test WER"}, {"type": "cer", "value": 0.1102657634184471, "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": "bas"}, "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 bas 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 #bas #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-bas-v1
================================


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


* Loss: 0.5997
* Wer: 0.3870


### 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-bas-v1 --dataset mozilla-foundation/common\_voice\_8\_0 --config bas --split test --log\_outputs


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


Basaa (bas) language isn't available in speech-recognition-community-v2/dev\_data


### 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: 500
* num\_epochs: 100
* 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-bas-v1 --dataset mozilla-foundation/common\_voice\_8\_0 --config bas --split test --log\_outputs


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


Basaa (bas) language isn't available in speech-recognition-community-v2/dev\_data ### 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: 500
* num\_epochs: 100
* 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 #bas #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-bas-v1 --dataset mozilla-foundation/common\_voice\_8\_0 --config bas --split test --log\_outputs


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


Basaa (bas) language isn't available in speech-recognition-community-v2/dev\_data ### 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: 500
* num\_epochs: 100
* 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 #bas #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-bas-v1 --dataset mozilla-foundation/common\_voice\_8\_0 --config bas --split test --log\_outputs


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


Basaa (bas) language isn't available in speech-recognition-community-v2/dev\_data### 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: 500
* num\_epochs: 100
* 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