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# wav2vec2-base-common-voice-50p-persian-colab

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0939
- Wer: 0.6537

## 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: 7.5e-05
- train_batch_size: 16
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.0437        | 2.52  | 600  | 3.0170          | 1.0    |
| 2.3667        | 5.04  | 1200 | 2.1575          | 0.9988 |
| 0.9565        | 7.56  | 1800 | 1.0801          | 0.8410 |
| 0.603         | 10.08 | 2400 | 0.9680          | 0.7678 |
| 0.507         | 12.61 | 3000 | 0.9554          | 0.7470 |
| 0.3754        | 15.13 | 3600 | 0.9524          | 0.7157 |
| 0.4267        | 17.65 | 4200 | 0.9290          | 0.6980 |
| 0.3308        | 20.17 | 4800 | 0.9557          | 0.7061 |
| 0.2259        | 22.69 | 5400 | 0.9864          | 0.6830 |
| 0.2486        | 25.21 | 6000 | 1.1086          | 0.6812 |
| 0.1956        | 27.73 | 6600 | 1.0497          | 0.6805 |
| 0.1835        | 30.25 | 7200 | 1.0660          | 0.6596 |
| 0.1926        | 32.77 | 7800 | 1.1274          | 0.6600 |
| 0.2765        | 35.29 | 8400 | 1.0882          | 0.6603 |
| 0.2397        | 37.82 | 9000 | 1.0939          | 0.6537 |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.10.0+cu113
- Datasets 1.18.3
- Tokenizers 0.10.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "wav2vec2-base-common-voice-50p-persian-colab", "results": []}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

wav2vec2-base-common-voice-50p-persian-colab
============================================


This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.0939
* Wer: 0.6537


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: 7.5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 1
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 2000
* num\_epochs: 40
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.0+cu113
* Datasets 1.18.3
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 7.5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 1
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 2000
* num\_epochs: 40
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.0+cu113
* Datasets 1.18.3
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 7.5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 1
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 2000
* num\_epochs: 40
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.0+cu113
* Datasets 1.18.3
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 7.5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 1
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 2000
* num\_epochs: 40
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.0+cu113
* Datasets 1.18.3
* Tokenizers 0.10.3