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# librispeech-5h-supervised

This model is a fine-tuned version of [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2041
- Wer: 0.0624

## 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: 16
- 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: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.7758        | 11.11 | 1000 | 0.3120          | 0.2337 |
| 0.1238        | 22.22 | 2000 | 0.1651          | 0.0826 |
| 0.0383        | 33.33 | 3000 | 0.1667          | 0.0712 |
| 0.023         | 44.44 | 4000 | 0.1893          | 0.0685 |
| 0.0166        | 55.56 | 5000 | 0.2008          | 0.0666 |
| 0.0131        | 66.67 | 6000 | 0.1942          | 0.0639 |
| 0.0106        | 77.78 | 7000 | 0.1979          | 0.0628 |
| 0.0091        | 88.89 | 8000 | 0.2027          | 0.0628 |
| 0.008         | 100.0 | 9000 | 0.2041          | 0.0624 |


### Framework versions

- Transformers 4.14.1
- Pytorch 1.10.2
- Datasets 1.18.2
- Tokenizers 0.10.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "librispeech-5h-supervised", "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 

librispeech-5h-supervised
=========================


This model is a fine-tuned version of facebook/wav2vec2-large-lv60 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2041
* Wer: 0.0624


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: 16
* 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: 100
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.14.1
* Pytorch 1.10.2
* Datasets 1.18.2
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 16
* 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: 100
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.14.1
* Pytorch 1.10.2
* Datasets 1.18.2
* Tokenizers 0.10.3
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: 0.0001
* train\_batch\_size: 16
* 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: 100
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.14.1
* Pytorch 1.10.2
* Datasets 1.18.2
* Tokenizers 0.10.3
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: 0.0001
* train\_batch\_size: 16
* 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: 100
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.14.1
* Pytorch 1.10.2
* Datasets 1.18.2
* Tokenizers 0.10.3