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# Nystrom-W2V2-100hrs-take-3

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 30.1649
- Wer: 0.1047

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 55.4504       | 9.01  | 1000  | 29.0675         | 0.1464 |
| 65.4799       | 18.02 | 2000  | 26.9263         | 0.1580 |
| 72.6609       | 27.03 | 3000  | 27.2220         | 0.1500 |
| 65.6264       | 36.04 | 4000  | 26.4758         | 0.1426 |
| 57.9496       | 45.04 | 5000  | 27.0818         | 0.1349 |
| 49.6643       | 54.05 | 6000  | 27.9658         | 0.1269 |
| 42.5205       | 63.06 | 7000  | 28.6973         | 0.1214 |
| 36.1799       | 72.07 | 8000  | 28.1021         | 0.1128 |
| 30.9742       | 81.08 | 9000  | 29.9000         | 0.1093 |
| 27.4728       | 90.09 | 10000 | 30.2661         | 0.1057 |
| 26.0383       | 99.1  | 11000 | 30.1649         | 0.1047 |


### 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-3", "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-3
==========================


This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 30.1649
* Wer: 0.1047


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