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# model-baru-collab-4

This model is a fine-tuned version of [zarko1231/model-baru-collab-3](https://huggingface.co/zarko1231/model-baru-collab-3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0326
- Wer: 0.3423

## 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: 0.0001
- train_batch_size: 50
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 100
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.9939        | 1.0   | 26   | 3.3198          | 1.0039 |
| 3.019         | 2.0   | 52   | 2.7545          | 1.0039 |
| 2.4572        | 3.0   | 78   | 1.7117          | 1.0587 |
| 1.3597        | 4.0   | 104  | 0.5751          | 1.0185 |
| 0.6395        | 5.0   | 130  | 0.2423          | 0.7125 |
| 0.3831        | 6.0   | 156  | 0.1320          | 0.5572 |
| 0.3083        | 7.0   | 182  | 0.0855          | 0.4575 |
| 0.2039        | 8.0   | 208  | 0.0603          | 0.3941 |
| 0.1589        | 9.0   | 234  | 0.0487          | 0.3787 |
| 0.2031        | 10.0  | 260  | 0.0442          | 0.3794 |
| 0.1396        | 11.0  | 286  | 0.0406          | 0.3655 |
| 0.1612        | 12.0  | 312  | 0.0390          | 0.3532 |
| 0.1285        | 13.0  | 338  | 0.0373          | 0.3509 |
| 0.1355        | 14.0  | 364  | 0.0356          | 0.3532 |
| 0.1527        | 15.0  | 390  | 0.0352          | 0.3478 |
| 0.1207        | 16.0  | 416  | 0.0339          | 0.3470 |
| 0.1106        | 17.0  | 442  | 0.0332          | 0.3462 |
| 0.1243        | 18.0  | 468  | 0.0332          | 0.3447 |
| 0.1107        | 19.0  | 494  | 0.0328          | 0.3447 |
| 0.0986        | 20.0  | 520  | 0.0326          | 0.3423 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "model-baru-collab-4", "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 

model-baru-collab-4
===================


This model is a fine-tuned version of zarko1231/model-baru-collab-3 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0326
* Wer: 0.3423


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: 0.0001
* train\_batch\_size: 50
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 100
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 50
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 100
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
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: 0.0001
* train\_batch\_size: 50
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 100
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3