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# wav2vec2-base-checkpoint-12

This model is a fine-tuned version of [jiobiala24/wav2vec2-base-checkpoint-11.1](https://huggingface.co/jiobiala24/wav2vec2-base-checkpoint-11.1) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0795
- Wer: 0.3452

## 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.2793        | 1.64  | 1000  | 0.5692          | 0.3518 |
| 0.2206        | 3.28  | 2000  | 0.6127          | 0.3460 |
| 0.1733        | 4.93  | 3000  | 0.6622          | 0.3580 |
| 0.1391        | 6.57  | 4000  | 0.6768          | 0.3519 |
| 0.1193        | 8.21  | 5000  | 0.7559          | 0.3540 |
| 0.1053        | 9.85  | 6000  | 0.7873          | 0.3562 |
| 0.093         | 11.49 | 7000  | 0.8170          | 0.3612 |
| 0.0833        | 13.14 | 8000  | 0.8682          | 0.3579 |
| 0.0753        | 14.78 | 9000  | 0.8317          | 0.3573 |
| 0.0698        | 16.42 | 10000 | 0.9213          | 0.3525 |
| 0.0623        | 18.06 | 11000 | 0.9746          | 0.3531 |
| 0.0594        | 19.7  | 12000 | 1.0027          | 0.3502 |
| 0.0538        | 21.35 | 13000 | 1.0045          | 0.3545 |
| 0.0504        | 22.99 | 14000 | 0.9821          | 0.3523 |
| 0.0461        | 24.63 | 15000 | 1.0818          | 0.3462 |
| 0.0439        | 26.27 | 16000 | 1.0995          | 0.3495 |
| 0.0421        | 27.91 | 17000 | 1.0533          | 0.3430 |
| 0.0415        | 29.56 | 18000 | 1.0795          | 0.3452 |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.10.0+cu111
- Datasets 1.13.3
- Tokenizers 0.10.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["common_voice"], "model-index": [{"name": "wav2vec2-base-checkpoint-12", "results": []}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition generated_from_trainer dataset:common_voice license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us 

wav2vec2-base-checkpoint-12
===========================


This model is a fine-tuned version of jiobiala24/wav2vec2-base-checkpoint-11.1 on the common\_voice dataset.
It achieves the following results on the evaluation set:


* Loss: 1.0795
* Wer: 0.3452


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: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 30
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.0+cu111
* Datasets 1.13.3
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 30
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.0+cu111
* Datasets 1.13.3
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 30
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.0+cu111
* Datasets 1.13.3
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 30
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.0+cu111
* Datasets 1.13.3
* Tokenizers 0.10.3