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# 

This model was trained from scratch on the librispeech_asr dataset.
It achieves the following results on the evaluation set:
- Loss: 5.2188
- Wer: 0.9238

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 20.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.7093        | 6.73  | 1500 | 5.7514          | 1.2104 |
| 5.642         | 13.45 | 3000 | 5.2188          | 0.9238 |


### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu113
- Datasets 1.18.3
- Tokenizers 0.11.0

{"tags": ["generated_from_trainer"], "datasets": ["librispeech_asr"], "model-index": [{"name": "", "results": []}]}
transformers pytorch tensorboard speech-encoder-decoder automatic-speech-recognition generated_from_trainer dataset:librispeech_asr endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #speech-encoder-decoder #automatic-speech-recognition #generated_from_trainer #dataset-librispeech_asr #endpoints_compatible #region-us 


This model was trained from scratch on the librispeech\_asr dataset.
It achieves the following results on the evaluation set:


* Loss: 5.2188
* Wer: 0.9238


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: 3e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 20.0
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu113
* Datasets 1.18.3
* Tokenizers 0.11.0



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 20.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu113
* Datasets 1.18.3
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #tensorboard #speech-encoder-decoder #automatic-speech-recognition #generated_from_trainer #dataset-librispeech_asr #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 20.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu113
* Datasets 1.18.3
* Tokenizers 0.11.0
passage: TAGS
#transformers #pytorch #tensorboard #speech-encoder-decoder #automatic-speech-recognition #generated_from_trainer #dataset-librispeech_asr #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 20.0
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu113
* Datasets 1.18.3
* Tokenizers 0.11.0