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# wav2vec2-xls-r-164m-id

This model is a fine-tuned version of [evanarlian/distil-wav2vec2-xls-r-164m-id](https://huggingface.co/evanarlian/distil-wav2vec2-xls-r-164m-id) on the evanarlian/common_voice_11_0_id_filtered dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2865
- Wer: 0.2923

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.3
- num_epochs: 80.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 1.4047        | 4.59  | 5000  | 1.0167          | 0.9138 |
| 0.587         | 9.18  | 10000 | 0.4639          | 0.5615 |
| 0.3782        | 13.77 | 15000 | 0.3375          | 0.4496 |
| 0.2867        | 18.37 | 20000 | 0.2881          | 0.4022 |
| 0.2519        | 22.96 | 25000 | 0.2775          | 0.3700 |
| 0.1941        | 27.55 | 30000 | 0.2701          | 0.3516 |
| 0.1727        | 32.14 | 35000 | 0.2795          | 0.3486 |
| 0.1448        | 36.73 | 40000 | 0.2878          | 0.3364 |
| 0.1251        | 41.32 | 45000 | 0.2649          | 0.3275 |
| 0.113         | 45.91 | 50000 | 0.2862          | 0.3168 |
| 0.0994        | 50.51 | 55000 | 0.2798          | 0.3091 |
| 0.0938        | 55.1  | 60000 | 0.2864          | 0.3070 |
| 0.0853        | 59.69 | 65000 | 0.2860          | 0.3069 |
| 0.0724        | 64.28 | 70000 | 0.2994          | 0.3003 |
| 0.0723        | 68.87 | 75000 | 0.2951          | 0.2983 |
| 0.0666        | 73.46 | 80000 | 0.2886          | 0.2941 |
| 0.0659        | 78.05 | 85000 | 0.2865          | 0.2923 |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2

{"tags": ["generated_from_trainer"], "datasets": ["evanarlian/common_voice_11_0_id_filtered"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2-xls-r-164m-id", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "evanarlian/common_voice_11_0_id_filtered", "type": "evanarlian/common_voice_11_0_id_filtered"}, "metrics": [{"type": "wer", "value": 0.2923162069919749, "name": "Wer"}]}]}]}
transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer dataset:evanarlian/common_voice_11_0_id_filtered model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-evanarlian/common_voice_11_0_id_filtered #model-index #endpoints_compatible #region-us 

wav2vec2-xls-r-164m-id
======================


This model is a fine-tuned version of evanarlian/distil-wav2vec2-xls-r-164m-id on the evanarlian/common\_voice\_11\_0\_id\_filtered dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2865
* Wer: 0.2923


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


More information needed


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


More information needed


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


More information needed


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


### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 24
* eval\_batch\_size: 24
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.3
* num\_epochs: 80.0
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu117
* Datasets 2.9.1.dev0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 24
* eval\_batch\_size: 24
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.3
* num\_epochs: 80.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu117
* Datasets 2.9.1.dev0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-evanarlian/common_voice_11_0_id_filtered #model-index #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 24
* eval\_batch\_size: 24
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.3
* num\_epochs: 80.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu117
* Datasets 2.9.1.dev0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-evanarlian/common_voice_11_0_id_filtered #model-index #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 24
* eval\_batch\_size: 24
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.3
* num\_epochs: 80.0
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu117
* Datasets 2.9.1.dev0
* Tokenizers 0.13.2