
# wav2vec2-large-xls-r-300m-assamese

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_7_0 dataset.
It achieves the following results on the evaluation set:

- WER: 0.7954545454545454
- CER: 0.32341269841269843

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

To compute the evaluation parameters

```bash
cd wav2vec2-large-xls-r-300m-assamese; python eval.py --model_id ./ --dataset mozilla-foundation/common_voice_7_0 --config as --split test --log_outputs
```

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:

- learning_rate: 3e-4
- train_batch_size: 16
- eval_batch_size: 8
- seed: not given
- 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: 400
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer      |
|:-------------:|:------:|:----:|:---------------:|:------:  |
| 1.584065      | NA     | 400  | 1.584065        | 0.915512 |
| 1.658865      | Na     | 800  | 1.658865        | 0.805096 |
| 1.882352      | NA     | 1200 | 1.882352        | 0.820742 |
| 1.881240      | NA     | 1600 | 1.881240        | 0.810907 |
| 2.159748      | NA     | 2000 | 2.159748        | 0.804202 |
| 1.992871      | NA     | 2400 | 1.992871        | 0.803308 |
| 2.201436      | NA     | 2800 | 2.201436        | 0.802861 |
| 2.165218      | NA     | 3200 | 2.165218        | 0.793920 |
| 2.253643      | NA     | 3600 | 2.253643        | 0.796603 |
| 2.265880      | NA     | 4000 | 2.265880        | 0.790344 |
| 2.293935      | NA     | 4400 | 2.293935        | 0.797050 |
| 2.288851      | NA     | 4800 | 2.288851        | 0.784086 |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.10.0+cu113
- Datasets 1.13.3
- Tokenizers 0.10.3

{"language": "as", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "speech", "xlsr-fine-tuning", "as", "robust-speech-event", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Assamese", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Common Voice 7", "type": "mozilla-foundation/common_voice_7_0", "args": "as"}, "metrics": [{"type": "wer", "value": 72.64, "name": "Test WER"}, {"type": "cer", "value": 27.35, "name": "Test CER"}]}]}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition audio speech xlsr-fine-tuning as robust-speech-event hf-asr-leaderboard dataset:mozilla-foundation/common_voice_7_0 license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning #as #robust-speech-event #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 

wav2vec2-large-xls-r-300m-assamese
==================================


This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common\_voice\_7\_0 dataset.
It achieves the following results on the evaluation set:


* WER: 0.7954545454545454
* CER: 0.32341269841269843


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


More information needed


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


More information needed


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


To compute the evaluation parameters


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


### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-4
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: not given
* 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: 400
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.0+cu113
* Datasets 1.13.3
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-4
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: not given
* 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: 400
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.0+cu113
* Datasets 1.13.3
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning #as #robust-speech-event #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-4
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: not given
* 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: 400
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.0+cu113
* Datasets 1.13.3
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning #as #robust-speech-event #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-4
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: not given
* 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: 400
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.0+cu113
* Datasets 1.13.3
* Tokenizers 0.10.3