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# finetune_teacher_babble_noise_mozilla_200_epochs

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: 71.8264
- Wer: 0.3574

## 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: 0.0005
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 256
- total_train_batch_size: 1024
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer    |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 149.8494      | 14.7   | 1000  | 41.8514         | 0.3998 |
| 101.5704      | 29.41  | 2000  | 41.9244         | 0.3942 |
| 87.7921       | 44.12  | 3000  | 44.8273         | 0.4013 |
| 74.0441       | 58.82  | 4000  | 48.9263         | 0.3976 |
| 61.9751       | 73.53  | 5000  | 48.6313         | 0.3950 |
| 51.4311       | 88.23  | 6000  | 52.6974         | 0.3915 |
| 42.7197       | 102.94 | 7000  | 51.2589         | 0.3862 |
| 35.5205       | 117.64 | 8000  | 57.6496         | 0.3841 |
| 29.2148       | 132.35 | 9000  | 64.6558         | 0.3745 |
| 24.4399       | 147.06 | 10000 | 62.6512         | 0.3692 |
| 20.5101       | 161.76 | 11000 | 67.4978         | 0.3625 |
| 18.0444       | 176.47 | 12000 | 72.0740         | 0.3584 |
| 16.681        | 191.18 | 13000 | 71.8264         | 0.3574 |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.12.1
- Datasets 2.7.1
- Tokenizers 0.11.0

{"tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "finetune_teacher_babble_noise_mozilla_200_epochs", "results": []}]}
transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #endpoints_compatible #has_space #region-us 

finetune\_teacher\_babble\_noise\_mozilla\_200\_epochs
======================================================


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


* Loss: 71.8264
* Wer: 0.3574


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: 0.0005
* train\_batch\_size: 4
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 256
* total\_train\_batch\_size: 1024
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_ratio: 0.2
* num\_epochs: 200
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.24.0
* Pytorch 1.12.1
* Datasets 2.7.1
* Tokenizers 0.11.0



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0005
* train\_batch\_size: 4
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 256
* total\_train\_batch\_size: 1024
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_ratio: 0.2
* num\_epochs: 200
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.24.0
* Pytorch 1.12.1
* Datasets 2.7.1
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #endpoints_compatible #has_space #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0005
* train\_batch\_size: 4
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 256
* total\_train\_batch\_size: 1024
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_ratio: 0.2
* num\_epochs: 200
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.24.0
* Pytorch 1.12.1
* Datasets 2.7.1
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #endpoints_compatible #has_space #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0005
* train\_batch\_size: 4
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 256
* total\_train\_batch\_size: 1024
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_ratio: 0.2
* num\_epochs: 200
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.24.0
* Pytorch 1.12.1
* Datasets 2.7.1
* Tokenizers 0.11.0