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# dgx1_w2v2_base_teacher_student_distillation_mozilla_epochs_100_batch_16

This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 33.1259
- Wer: 0.9996

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 128
- total_train_batch_size: 2048
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 81.3268       | 7.35  | 500  | 27.8835         | 0.9996 |
| 62.2215       | 14.7  | 1000 | 28.9444         | 0.9997 |
| 58.4422       | 22.06 | 1500 | 30.4689         | 0.9997 |
| 55.5853       | 29.41 | 2000 | 30.3907         | 0.9996 |
| 53.3674       | 36.76 | 2500 | 31.5643         | 0.9996 |
| 51.3963       | 44.12 | 3000 | 31.6585         | 0.9996 |
| 49.5487       | 51.47 | 3500 | 33.0177         | 0.9996 |
| 48.3909       | 58.82 | 4000 | 33.6293         | 0.9996 |
| 47.6249       | 66.18 | 4500 | 33.1259         | 0.9996 |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.8.0
- Tokenizers 0.13.2
{"language": ["en"], "tags": ["generated_from_trainer"], "datasets": ["mozilla-foundation/common_voice_11_0"], "metrics": ["wer"], "model-index": [{"name": "dgx1_w2v2_base_teacher_student_distillation_mozilla_epochs_100_batch_16", "results": []}]}
transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer en dataset:mozilla-foundation/common_voice_11_0 endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #en #dataset-mozilla-foundation/common_voice_11_0 #endpoints_compatible #region-us 

dgx1\_w2v2\_base\_teacher\_student\_distillation\_mozilla\_epochs\_100\_batch\_16
=================================================================================


This model is a fine-tuned version of [](URL on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 33.1259
* Wer: 0.9996


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: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 128
* total\_train\_batch\_size: 2048
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.2
* num\_epochs: 100
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.25.1
* Pytorch 1.12.1
* Datasets 2.8.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 128
* total\_train\_batch\_size: 2048
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.2
* num\_epochs: 100
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.25.1
* Pytorch 1.12.1
* Datasets 2.8.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #en #dataset-mozilla-foundation/common_voice_11_0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 128
* total\_train\_batch\_size: 2048
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.2
* num\_epochs: 100
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.25.1
* Pytorch 1.12.1
* Datasets 2.8.0
* Tokenizers 0.13.2