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# Nystrom-W2V2-100hrs-take-4-unfreeze-extractor-try-2

This model is a fine-tuned version of [rohitp1/Nystrom-W2V2-100hrs-take-4-unfreeze-extractor](https://huggingface.co/rohitp1/Nystrom-W2V2-100hrs-take-4-unfreeze-extractor) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 27.1915
- Wer: 0.0869

## 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: 64
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 23.1458       | 9.01  | 1000  | 28.9573         | 0.1039 |
| 32.7156       | 18.02 | 2000  | 25.6155         | 0.1218 |
| 43.506        | 27.03 | 3000  | 27.6332         | 0.1228 |
| 43.3608       | 36.04 | 4000  | 26.0539         | 0.1169 |
| 39.984        | 45.04 | 5000  | 25.9836         | 0.1137 |
| 35.1977       | 54.05 | 6000  | 26.2060         | 0.1077 |
| 30.1951       | 63.06 | 7000  | 27.0999         | 0.1033 |
| 25.7519       | 72.07 | 8000  | 27.8459         | 0.0964 |
| 22.1982       | 81.08 | 9000  | 27.9773         | 0.0908 |
| 20.0551       | 90.09 | 10000 | 27.4222         | 0.0884 |
| 19.4505       | 99.1  | 11000 | 27.1915         | 0.0869 |


### 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": "Nystrom-W2V2-100hrs-take-4-unfreeze-extractor-try-2", "results": []}]}
transformers pytorch wav2vec2 generated_from_trainer endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #generated_from_trainer #endpoints_compatible #region-us 

Nystrom-W2V2-100hrs-take-4-unfreeze-extractor-try-2
===================================================


This model is a fine-tuned version of rohitp1/Nystrom-W2V2-100hrs-take-4-unfreeze-extractor on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 27.1915
* Wer: 0.0869


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: 64
* total\_train\_batch\_size: 256
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_ratio: 0.2
* num\_epochs: 100
* 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: 64
* total\_train\_batch\_size: 256
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_ratio: 0.2
* num\_epochs: 100
* 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 #generated_from_trainer #endpoints_compatible #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: 64
* total\_train\_batch\_size: 256
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_ratio: 0.2
* num\_epochs: 100
* 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 #generated_from_trainer #endpoints_compatible #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: 64
* total\_train\_batch\_size: 256
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_ratio: 0.2
* num\_epochs: 100
* 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