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# wav2vec2-model2-torgo

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 4.9975
- Wer: 1.0

## 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: 0.1
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:---:|
| 12.5453       | 0.76  | 500   | 14.6490         | 1.0 |
| 4.8036        | 1.53  | 1000  | 8.4523          | 1.0 |
| 5.0421        | 2.29  | 1500  | 5.4114          | 1.0 |
| 5.2055        | 3.05  | 2000  | 11.0507         | 1.0 |
| 4.6389        | 3.82  | 2500  | 4.6792          | 1.0 |
| 4.5523        | 4.58  | 3000  | 4.7855          | 1.0 |
| 4.7843        | 5.34  | 3500  | 11.2783         | 1.0 |
| 4.6066        | 6.11  | 4000  | 8.7807          | 1.0 |
| 4.7382        | 6.87  | 4500  | 2942.0220       | 1.0 |
| 130.5733      | 7.63  | 5000  | 5.8412          | 1.0 |
| 4.4972        | 8.4   | 5500  | 17.7038         | 1.0 |
| 4.5196        | 9.16  | 6000  | 11.4548         | 1.0 |
| 4.3198        | 9.92  | 6500  | 6.0885          | 1.0 |
| 4.4273        | 10.69 | 7000  | 6.7374          | 1.0 |
| 4.2783        | 11.45 | 7500  | 4.7276          | 1.0 |
| 4.2985        | 12.21 | 8000  | 6.1412          | 1.0 |
| 4.3262        | 12.98 | 8500  | 5.2621          | 1.0 |
| 4.1705        | 13.74 | 9000  | 5.2214          | 1.0 |
| 4.3176        | 14.5  | 9500  | 5.5359          | 1.0 |
| 3.9808        | 15.27 | 10000 | 4.1537          | 1.0 |
| 4.0228        | 16.03 | 10500 | 4.2962          | 1.0 |
| 4.0595        | 16.79 | 11000 | 7.6361          | 1.0 |
| 4.0088        | 17.56 | 11500 | 6.8715          | 1.0 |
| 3.8727        | 18.32 | 12000 | 8.8657          | 1.0 |
| 4.0073        | 19.08 | 12500 | 5.8170          | 1.0 |
| 3.8511        | 19.85 | 13000 | 13.9836         | 1.0 |
| 4.0899        | 20.61 | 13500 | 5.3287          | 1.0 |
| 3.8782        | 21.37 | 14000 | 8.0635          | 1.0 |
| 3.9235        | 22.14 | 14500 | 5.5129          | 1.0 |
| 3.7276        | 22.9  | 15000 | 5.0819          | 1.0 |
| 3.7908        | 23.66 | 15500 | 6.1458          | 1.0 |
| 3.9176        | 24.43 | 16000 | 4.6094          | 1.0 |
| 3.8477        | 25.19 | 16500 | 5.1406          | 1.0 |
| 3.6917        | 25.95 | 17000 | 4.5684          | 1.0 |
| 3.8568        | 26.72 | 17500 | 4.0306          | 1.0 |
| 3.7231        | 27.48 | 18000 | 5.6331          | 1.0 |
| 3.8145        | 28.24 | 18500 | 8.2997          | 1.0 |
| 3.7809        | 29.01 | 19000 | 5.7468          | 1.0 |
| 3.5995        | 29.77 | 19500 | 4.9975          | 1.0 |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0
- Datasets 1.18.3
- Tokenizers 0.11.6

{"tags": ["generated_from_trainer"], "model-index": [{"name": "wav2vec2-model2-torgo", "results": []}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition generated_from_trainer endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #endpoints_compatible #region-us 

wav2vec2-model2-torgo
=====================


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


* Loss: 4.9975
* Wer: 1.0


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: 0.1
* train\_batch\_size: 1
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 4
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 30


### Training results



### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0
* Datasets 1.18.3
* Tokenizers 0.11.6



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.1
* train\_batch\_size: 1
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 4
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0
* Datasets 1.18.3
* Tokenizers 0.11.6
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.1
* train\_batch\_size: 1
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 4
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0
* Datasets 1.18.3
* Tokenizers 0.11.6
passage: TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.1
* train\_batch\_size: 1
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 4
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 30### Training results### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0
* Datasets 1.18.3
* Tokenizers 0.11.6