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# wav2vec2-base

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: 3.0808
- Wer: 1.0

## 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: 4
- 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: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:---:|
| 3.7118        | 0.5   | 500   | 3.0635          | 1.0 |
| 2.9533        | 1.01  | 1000  | 3.0383          | 1.0 |
| 2.9493        | 1.51  | 1500  | 3.0638          | 1.0 |
| 2.9495        | 2.01  | 2000  | 3.0554          | 1.0 |
| 2.9468        | 2.51  | 2500  | 3.0630          | 1.0 |
| 2.9493        | 3.02  | 3000  | 3.0530          | 1.0 |
| 2.9457        | 3.52  | 3500  | 3.0534          | 1.0 |
| 2.9492        | 4.02  | 4000  | 3.0357          | 1.0 |
| 2.9444        | 4.52  | 4500  | 3.0366          | 1.0 |
| 2.9495        | 5.03  | 5000  | 3.0412          | 1.0 |
| 2.9468        | 5.53  | 5500  | 3.0331          | 1.0 |
| 2.9453        | 6.03  | 6000  | 3.0847          | 1.0 |
| 2.9484        | 6.53  | 6500  | 3.0661          | 1.0 |
| 2.9457        | 7.04  | 7000  | 3.0769          | 1.0 |
| 2.9449        | 7.54  | 7500  | 3.0701          | 1.0 |
| 2.9453        | 8.04  | 8000  | 3.1072          | 1.0 |
| 2.9436        | 8.54  | 8500  | 3.1043          | 1.0 |
| 2.9474        | 9.05  | 9000  | 3.0902          | 1.0 |
| 2.9452        | 9.55  | 9500  | 3.0879          | 1.0 |
| 2.9443        | 10.05 | 10000 | 3.1112          | 1.0 |
| 2.9436        | 10.55 | 10500 | 3.0946          | 1.0 |
| 2.9469        | 11.06 | 11000 | 3.0812          | 1.0 |
| 2.9434        | 11.56 | 11500 | 3.1112          | 1.0 |
| 2.9442        | 12.06 | 12000 | 3.0855          | 1.0 |
| 2.9436        | 12.56 | 12500 | 3.0786          | 1.0 |
| 2.9425        | 13.07 | 13000 | 3.0789          | 1.0 |
| 2.9418        | 13.57 | 13500 | 3.0786          | 1.0 |
| 2.9443        | 14.07 | 14000 | 3.0798          | 1.0 |
| 2.9449        | 14.57 | 14500 | 3.0808          | 1.0 |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.10.2
- Datasets 1.18.3
- Tokenizers 0.10.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "wav2vec2-base", "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
=============


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: 3.0808
* Wer: 1.0


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: 4
* 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: 15
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.2
* Datasets 1.18.3
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 4
* 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: 15
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.2
* 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: 0.0001
* train\_batch\_size: 4
* 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: 15
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.2
* 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: 0.0001
* train\_batch\_size: 4
* 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: 15
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.2
* Datasets 1.18.3
* Tokenizers 0.10.3