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# wav2vec2-19

WER 0.283

WER 0.126 with 5-Gram

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: 0.6305
- Wer: 0.4499

## 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: 0.0003
- 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: 800
- num_epochs: 60

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.4816        | 2.74  | 400  | 1.0717          | 0.8927 |
| 0.751         | 5.48  | 800  | 0.7155          | 0.7533 |
| 0.517         | 8.22  | 1200 | 0.7039          | 0.6675 |
| 0.3988        | 10.96 | 1600 | 0.5935          | 0.6149 |
| 0.3179        | 13.7  | 2000 | 0.6477          | 0.5999 |
| 0.2755        | 16.44 | 2400 | 0.5549          | 0.5798 |
| 0.2343        | 19.18 | 2800 | 0.6626          | 0.5798 |
| 0.2103        | 21.92 | 3200 | 0.6488          | 0.5674 |
| 0.1877        | 24.66 | 3600 | 0.5874          | 0.5339 |
| 0.1719        | 27.4  | 4000 | 0.6354          | 0.5389 |
| 0.1603        | 30.14 | 4400 | 0.6612          | 0.5210 |
| 0.1401        | 32.88 | 4800 | 0.6676          | 0.5131 |
| 0.1286        | 35.62 | 5200 | 0.6366          | 0.5075 |
| 0.1159        | 38.36 | 5600 | 0.6064          | 0.4977 |
| 0.1084        | 41.1  | 6000 | 0.6530          | 0.4835 |
| 0.0974        | 43.84 | 6400 | 0.6118          | 0.4853 |
| 0.0879        | 46.58 | 6800 | 0.6316          | 0.4770 |
| 0.0815        | 49.32 | 7200 | 0.6125          | 0.4664 |
| 0.0708        | 52.05 | 7600 | 0.6449          | 0.4683 |
| 0.0651        | 54.79 | 8000 | 0.6068          | 0.4571 |
| 0.0555        | 57.53 | 8400 | 0.6305          | 0.4499 |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "wav2vec2-19", "results": []}]}
transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

wav2vec2-19
===========


WER 0.283


WER 0.126 with 5-Gram


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: 0.6305
* Wer: 0.4499


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: 0.0003
* 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: 800
* num\_epochs: 60


### Training results



### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* 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: 800
* num\_epochs: 60 ### Training results ### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #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: 0.0003
* 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: 800
* num\_epochs: 60 ### Training results ### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #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: 0.0003
* 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: 800
* num\_epochs: 60### Training results### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1