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# libri-alpha-0.75-Temp-1-att-take-2

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 44.5402
- Wer: 0.1081

## 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 118.8957      | 0.45  | 400  | 46.1043         | 0.1056 |
| 118.7076      | 0.9   | 800  | 44.1911         | 0.1037 |
| 106.9074      | 1.35  | 1200 | 42.3038         | 0.1028 |
| 107.4129      | 1.79  | 1600 | 48.0483         | 0.1030 |
| 106.3615      | 2.24  | 2000 | 60.1421         | 0.1029 |
| 106.3024      | 2.69  | 2400 | 48.8849         | 0.1028 |
| 107.8432      | 3.14  | 2800 | 42.9345         | 0.1072 |
| 107.6928      | 3.59  | 3200 | 44.5402         | 0.1081 |


### Framework versions

- Transformers 4.23.1
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.1

{"tags": ["generated_from_trainer"], "model-index": [{"name": "libri-alpha-0.75-Temp-1-att-take-2", "results": []}]}
transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #endpoints_compatible #region-us 

libri-alpha-0.75-Temp-1-att-take-2
==================================


This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 44.5402
* Wer: 0.1081


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: 0.0002
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.2
* num\_epochs: 40
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.23.1
* Pytorch 1.12.1
* Datasets 2.6.1
* Tokenizers 0.13.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.2
* num\_epochs: 40
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.23.1
* Pytorch 1.12.1
* Datasets 2.6.1
* Tokenizers 0.13.1
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.2
* num\_epochs: 40
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.23.1
* Pytorch 1.12.1
* Datasets 2.6.1
* Tokenizers 0.13.1
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.2
* num\_epochs: 40
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.23.1
* Pytorch 1.12.1
* Datasets 2.6.1
* Tokenizers 0.13.1