
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# dgx2_w2v2_large_distill_noisy_teacher_mozilla_epochs_50_batch_16

This model is a fine-tuned version of [rohitp1/kkkh_w2v2_large_finetune_teacher_babble_noise_mozilla_50_epochs_batch_16](https://huggingface.co/rohitp1/kkkh_w2v2_large_finetune_teacher_babble_noise_mozilla_50_epochs_batch_16) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 21652.1836
- Wer: 0.2592

## 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: 256
- total_train_batch_size: 4096
- 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 74637.3574    | 7.31  | 250  | 4331.1958       | 0.2791 |
| 75858.376     | 14.63 | 500  | 7166.9727       | 0.2759 |
| 76494.272     | 21.94 | 750  | 9417.4209       | 0.2713 |
| 76375.128     | 29.26 | 1000 | 13408.2549      | 0.2680 |
| 74149.512     | 36.57 | 1250 | 14529.0449      | 0.2657 |
| 73472.352     | 43.89 | 1500 | 14684.6582      | 0.2643 |
| 72301.832     | 51.2  | 1750 | 15828.4707      | 0.2634 |
| 71340.256     | 58.51 | 2000 | 17094.2773      | 0.2614 |
| 71890.376     | 65.83 | 2250 | 17973.5566      | 0.2604 |
| 71789.656     | 73.14 | 2500 | 19330.4316      | 0.2599 |
| 71579.512     | 80.46 | 2750 | 19927.2129      | 0.2599 |
| 71862.48      | 87.77 | 3000 | 21301.7754      | 0.2592 |
| 71131.112     | 95.09 | 3250 | 21652.1836      | 0.2592 |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.0+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "dgx2_w2v2_large_distill_noisy_teacher_mozilla_epochs_50_batch_16", "results": []}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

dgx2\_w2v2\_large\_distill\_noisy\_teacher\_mozilla\_epochs\_50\_batch\_16
==========================================================================


This model is a fine-tuned version of rohitp1/kkkh\_w2v2\_large\_finetune\_teacher\_babble\_noise\_mozilla\_50\_epochs\_batch\_16 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 21652.1836
* Wer: 0.2592


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: 256
* total\_train\_batch\_size: 4096
* 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 4.29.2
* Pytorch 2.0.0+cu117
* 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: 256
* total\_train\_batch\_size: 4096
* 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 4.29.2
* Pytorch 2.0.0+cu117
* Datasets 2.8.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #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: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 256
* total\_train\_batch\_size: 4096
* 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 4.29.2
* Pytorch 2.0.0+cu117
* Datasets 2.8.0
* Tokenizers 0.13.2