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# 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

### 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-bg-d2 --dataset mozilla-foundation/common_voice_8_0 --config bg --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-bg-d2 --dataset speech-recognition-community-v2/dev_data --config bg --split validation --chunk_length_s 10 --stride_length_s 1
    
### 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": ["bg"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "bg", "generated_from_trainer", "hf-asr-leaderboard", "mozilla-foundation/common_voice_8_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-bg-d2", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Common Voice 8", "type": "mozilla-foundation/common_voice_8_0", "args": "bg"}, "metrics": [{"type": "wer", "value": 0.28775471338792613, "name": "Test WER"}, {"type": "cer", "value": 0.06861971204625049, "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": "bg"}, "metrics": [{"type": "wer", "value": 0.49783147459727384, "name": "Test WER"}, {"type": "cer", "value": 0.1591062599627158, "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": "bg"}, "metrics": [{"type": "wer", "value": 51.25, "name": "Test WER"}]}]}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition bg generated_from_trainer hf-asr-leaderboard mozilla-foundation/common_voice_8_0 robust-speech-event 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 #bg #generated_from_trainer #hf-asr-leaderboard #mozilla-foundation/common_voice_8_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 

wav2vec2-large-xls-r-300m-bg-d2
===============================


This model is a fine-tuned version of 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


### 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-bg-d2 --dataset mozilla-foundation/common\_voice\_8\_0 --config bg --split test --log\_outputs


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


python URL --model\_id DrishtiSharma/wav2vec2-large-xls-r-300m-bg-d2 --dataset speech-recognition-community-v2/dev\_data --config bg --split validation --chunk\_length\_s 10 --stride\_length\_s 1


### 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



### 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-bg-d2 --dataset mozilla-foundation/common\_voice\_8\_0 --config bg --split test --log\_outputs


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


python URL --model\_id DrishtiSharma/wav2vec2-large-xls-r-300m-bg-d2 --dataset speech-recognition-community-v2/dev\_data --config bg --split validation --chunk\_length\_s 10 --stride\_length\_s 1 ### 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 ### 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 #bg #generated_from_trainer #hf-asr-leaderboard #mozilla-foundation/common_voice_8_0 #robust-speech-event #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-bg-d2 --dataset mozilla-foundation/common\_voice\_8\_0 --config bg --split test --log\_outputs


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


python URL --model\_id DrishtiSharma/wav2vec2-large-xls-r-300m-bg-d2 --dataset speech-recognition-community-v2/dev\_data --config bg --split validation --chunk\_length\_s 10 --stride\_length\_s 1 ### 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 ### 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 #bg #generated_from_trainer #hf-asr-leaderboard #mozilla-foundation/common_voice_8_0 #robust-speech-event #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-bg-d2 --dataset mozilla-foundation/common\_voice\_8\_0 --config bg --split test --log\_outputs


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


python URL --model\_id DrishtiSharma/wav2vec2-large-xls-r-300m-bg-d2 --dataset speech-recognition-community-v2/dev\_data --config bg --split validation --chunk\_length\_s 10 --stride\_length\_s 1### 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