# sammy786/wav2vec2-xlsr-romansh_vallader

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 - rm-vallader dataset.
It achieves the following results on evaluation set (which is 10 percent of train data set merged with other and dev datasets):
- Loss: 30.31
- Wer: 26.32

## 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: 40
- mixed_precision_training: Native AMP


### Training results


| Step | Training Loss | Validation Loss | Wer      |
|------|---------------|-----------------|----------|
| 200  | 5.895100      | 3.136624        | 0.999713 |
| 400  | 1.545700      | 0.445069        | 0.471584 |
| 600  | 0.693900      | 0.340700        | 0.363088 |
| 800  | 0.510600      | 0.295432        | 0.289610 |
| 1000 | 0.318800      | 0.286795        | 0.281860 |
| 1200 | 0.194000      | 0.307468        | 0.274110 |
| 1400 | 0.151800      | 0.304849        | 0.264351 |
| 1600 | 0.148300      | 0.303112        | 0.263203 |



### 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-romansh_vallader --dataset mozilla-foundation/common_voice_8_0 --config rm-vallader --split test
```
{"language": ["rm-vallader"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "model_for_talk", "mozilla-foundation/common_voice_8_0", "rm-vallader", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "sammy786/wav2vec2-xlsr-romansh_vallader", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Common Voice 8", "type": "mozilla-foundation/common_voice_8_0", "args": "rm-vallader"}, "metrics": [{"type": "wer", "value": 28.54, "name": "Test WER"}, {"type": "cer", "value": 6.57, "name": "Test CER"}]}]}]}
transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer hf-asr-leaderboard model_for_talk mozilla-foundation/common_voice_8_0 rm-vallader robust-speech-event dataset:mozilla-foundation/common_voice_8_0 license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #rm-vallader #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 

sammy786/wav2vec2-xlsr-romansh\_vallader
========================================


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


* Loss: 30.31
* Wer: 26.32


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: 40
* 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: 40
* 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 #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #rm-vallader #robust-speech-event #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: 40
* 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 #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #rm-vallader #robust-speech-event #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: 40
* 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'