
# Akashpb13/Swahili_xlsr

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_7_0 - hu dataset.
It achieves the following results on the evaluation set (which is 10 percent of train data set merged with dev datasets):
- Loss: 0.159032
- Wer: 0.187934
## Model description
"facebook/wav2vec2-xls-r-300m" was finetuned.

## Intended uses & limitations
More information needed
## Training and evaluation data
Training data - 
Common voice Hausa train.tsv and dev.tsv
Only those points were considered where upvotes were greater than downvotes and duplicates were removed after concatenation of all the datasets given in common voice 7.0

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

### Training hyperparameters

The following hyperparameters were used during training:

- learning_rate: 0.000096
- train_batch_size: 16
- eval_batch_size: 16
- seed: 13
- gradient_accumulation_steps: 2
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 500
- num_epochs: 80
- mixed_precision_training: Native AMP


### Training results

| Step | Training Loss | Validation Loss | Wer      |
|------|---------------|-----------------|----------|
| 500  | 4.810000      | 2.168847        | 0.995747 |
| 1000 | 0.564200      | 0.209411        | 0.303485 |
| 1500 | 0.217700      | 0.153959        | 0.239534 |
| 2000 | 0.150700      | 0.139901        | 0.216327 |
| 2500 | 0.119400      | 0.137543        | 0.208828 |
| 3000 | 0.099500      | 0.140921        | 0.203045 |
| 3500 | 0.087100      | 0.138835        | 0.199649 |
| 4000 | 0.074600      | 0.141297        | 0.195844 |
| 4500 | 0.066600      | 0.148560        | 0.194127 |
| 5000 | 0.060400      | 0.151214        | 0.194388 |
| 5500 | 0.054400      | 0.156072        | 0.192187 |
| 6000 | 0.051100      | 0.154726        | 0.190322 |
| 6500 | 0.048200      | 0.159847        | 0.189538 |
| 7000 | 0.046400      | 0.158727        | 0.188307 |
| 7500 | 0.046500      | 0.159032        | 0.187934 |


### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.0+cu102
- Datasets 1.18.3
- 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 Akashpb13/Swahili_xlsr --dataset mozilla-foundation/common_voice_8_0 --config sw --split test
```


{"language": ["sw"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "model_for_talk", "mozilla-foundation/common_voice_8_0", "robust-speech-event", "sw"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "Akashpb13/Swahili_xlsr", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Common Voice 8", "type": "mozilla-foundation/common_voice_8_0", "args": "sw"}, "metrics": [{"type": "wer", "value": 0.11763625454589981, "name": "Test WER"}, {"type": "cer", "value": 0.02884228669922436, "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": "kmr"}, "metrics": [{"type": "wer", "value": 0.11763625454589981, "name": "Test WER"}, {"type": "cer", "value": 0.02884228669922436, "name": "Test CER"}]}]}]}
transformers pytorch safetensors wav2vec2 automatic-speech-recognition generated_from_trainer hf-asr-leaderboard model_for_talk mozilla-foundation/common_voice_8_0 robust-speech-event sw dataset:mozilla-foundation/common_voice_8_0 license:apache-2.0 model-index endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #safetensors #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #robust-speech-event #sw #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us 

Akashpb13/Swahili\_xlsr
=======================


This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - hu dataset.
It achieves the following results on the evaluation set (which is 10 percent of train data set merged with dev datasets):


* Loss: 0.159032
* Wer: 0.187934


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


"facebook/wav2vec2-xls-r-300m" was finetuned.


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


More information needed


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


Training data -
Common voice Hausa URL and URL
Only those points were considered where upvotes were greater than downvotes and duplicates were removed after concatenation of all the datasets given in common voice 7.0


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


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


### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.000096
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 13
* gradient\_accumulation\_steps: 2
* lr\_scheduler\_type: cosine\_with\_restarts
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 80
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.0+cu102
* Datasets 1.18.3
* 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: 0.000096
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 13
* gradient\_accumulation\_steps: 2
* lr\_scheduler\_type: cosine\_with\_restarts
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 80
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.0+cu102
* Datasets 1.18.3
* Tokenizers 0.10.3 #### Evaluation Commands


1. To evaluate on 'mozilla-foundation/common\_voice\_8\_0' with split 'test'
TAGS
#transformers #pytorch #safetensors #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #robust-speech-event #sw #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.000096
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 13
* gradient\_accumulation\_steps: 2
* lr\_scheduler\_type: cosine\_with\_restarts
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 80
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.0+cu102
* Datasets 1.18.3
* Tokenizers 0.10.3 #### Evaluation Commands


1. To evaluate on 'mozilla-foundation/common\_voice\_8\_0' with split 'test'
passage: TAGS
#transformers #pytorch #safetensors #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #robust-speech-event #sw #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.000096
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 13
* gradient\_accumulation\_steps: 2
* lr\_scheduler\_type: cosine\_with\_restarts
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 80
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.0+cu102
* Datasets 1.18.3
* Tokenizers 0.10.3#### Evaluation Commands


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