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

This model is a fine-tuned version of [rohitp1/Nystrom-W2V2-100hrs-take-3](https://huggingface.co/rohitp1/Nystrom-W2V2-100hrs-take-3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 27.1839
- Wer: 0.0915

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 30.9159       | 9.01  | 1000  | 27.2422         | 0.1205 |
| 47.7101       | 18.02 | 2000  | 25.0538         | 0.1366 |
| 61.5118       | 27.03 | 3000  | 25.3063         | 0.1343 |
| 57.2966       | 36.04 | 4000  | 25.0429         | 0.1276 |
| 50.7161       | 45.04 | 5000  | 27.2507         | 0.1235 |
| 43.7605       | 54.05 | 6000  | 25.9086         | 0.1145 |
| 36.8698       | 63.06 | 7000  | 26.4890         | 0.1085 |
| 31.0921       | 72.07 | 8000  | 26.9372         | 0.1021 |
| 26.4249       | 81.08 | 9000  | 27.8031         | 0.0961 |
| 23.336        | 90.09 | 10000 | 27.2129         | 0.0928 |
| 22.2249       | 99.1  | 11000 | 27.1839         | 0.0915 |


### 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", "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
=============================================


This model is a fine-tuned version of rohitp1/Nystrom-W2V2-100hrs-take-3 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 27.1839
* Wer: 0.0915


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