# sammy786/wav2vec2-xlsr-interlingua

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - ia dataset.
It achieves the following results on evaluation set (which is 10 percent of train data set merged with other and dev datasets):
- Loss: 5.44
- Wer: 19.78

## Model description
"facebook/wav2vec2-xls-r-1b" was finetuned.

## Intended uses & limitations
More information needed
## Training and evaluation data
Training data - 
Common voice Finnish train.tsv, dev.tsv and other.tsv

## Training procedure
For creating the train dataset, all possible datasets were appended and 90-10 split was used. 

### Training hyperparameters

The following hyperparameters were used during training:

- learning_rate: 0.000045637994662983496
- train_batch_size: 16
- eval_batch_size: 16
- seed: 13
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP


### Training results


| Step | Training Loss | Validation Loss | Wer      |
|------|---------------|-----------------|----------|
| 200  | 4.649200      | 0.483339        | 0.511322 |
| 400  | 0.764700      | 0.133428        | 0.251288 |
| 600  | 0.563700      | 0.099292        | 0.227745 |
| 800  | 0.438800      | 0.087545        | 0.217445 |
| 1000 | 0.406800      | 0.072313        | 0.213848 |
| 1200 | 0.237500      | 0.066965        | 0.213766 |
| 1400 | 0.177800      | 0.064419        | 0.208126 |
| 1600 | 0.157100      | 0.065962        | 0.214011 |
| 1800 | 0.146600      | 0.059477        | 0.202076 |
| 2000 | 0.132800      | 0.055015        | 0.201831 |
| 2200 | 0.122000      | 0.055421        | 0.201749 |
| 2400 | 0.115700      | 0.054462        | 0.197826 |



### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.0+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.10.3

#### Evaluation Commands

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

```bash
python eval.py --model_id sammy786/wav2vec2-xlsr-interlingua --dataset mozilla-foundation/common_voice_8_0 --config ia --split test
```
{"language": ["ia"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "ia", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "sammy786/wav2vec2-xlsr-interlingua", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Common Voice 8", "type": "mozilla-foundation/common_voice_8_0", "args": "ia"}, "metrics": [{"type": "wer", "value": 16.81, "name": "Test WER"}, {"type": "cer", "value": 4.76, "name": "Test CER"}]}]}]}
transformers pytorch wav2vec2 automatic-speech-recognition mozilla-foundation/common_voice_8_0 generated_from_trainer ia 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 #ia #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 

sammy786/wav2vec2-xlsr-interlingua
==================================


This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - ia dataset.
It achieves the following results on evaluation set (which is 10 percent of train data set merged with other and dev datasets):


* Loss: 5.44
* Wer: 19.78


Model description
-----------------


"facebook/wav2vec2-xls-r-1b" was finetuned.


Intended uses & limitations
---------------------------


More information needed


Training and evaluation data
----------------------------


Training data -
Common voice Finnish URL, URL and URL


Training procedure
------------------


For creating the train dataset, all possible datasets were appended and 90-10 split was used.


### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.000045637994662983496
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 13
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine\_with\_restarts
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 30
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.0+cu102
* Datasets 1.17.1.dev0
* Tokenizers 0.10.3


#### Evaluation Commands


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



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.000045637994662983496
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 13
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine\_with\_restarts
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 30
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.0+cu102
* Datasets 1.17.1.dev0
* Tokenizers 0.10.3 #### Evaluation Commands


1. To evaluate on 'mozilla-foundation/common\_voice\_8\_0' with split 'test'
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #ia #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: 0.000045637994662983496
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 13
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine\_with\_restarts
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 30
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.0+cu102
* Datasets 1.17.1.dev0
* Tokenizers 0.10.3 #### Evaluation Commands


1. To evaluate on 'mozilla-foundation/common\_voice\_8\_0' with split 'test'
passage: TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #ia #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: 0.000045637994662983496
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 13
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine\_with\_restarts
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 30
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.0+cu102
* Datasets 1.17.1.dev0
* Tokenizers 0.10.3#### Evaluation Commands


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