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# mounir4

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6829
- Wer: 1

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer |
|:-------------:|:------:|:-----:|:---------------:|:---:|
| 3.3494        | 8.51   | 500   | 3.1482          | 1   |
| 2.9331        | 17.02  | 1000  | 2.9053          | 1   |
| 2.8691        | 25.53  | 1500  | 2.8793          | 1   |
| 2.8393        | 34.04  | 2000  | 2.8696          | 1   |
| 1.9588        | 42.55  | 2500  | 1.5982          | 1   |
| 0.9108        | 51.06  | 3000  | 0.8335          | 1   |
| 0.7196        | 59.57  | 3500  | 0.7443          | 1   |
| 0.6198        | 68.09  | 4000  | 0.6949          | 1   |
| 0.5558        | 76.6   | 4500  | 0.6862          | 1   |
| 0.5152        | 85.11  | 5000  | 0.6743          | 1   |
| 0.4781        | 93.62  | 5500  | 0.6668          | 1   |
| 0.4442        | 102.13 | 6000  | 0.6587          | 1   |
| 0.4255        | 110.64 | 6500  | 0.6498          | 1   |
| 0.408         | 119.15 | 7000  | 0.6698          | 1   |
| 0.3888        | 127.66 | 7500  | 0.6739          | 1   |
| 0.3815        | 136.17 | 8000  | 0.6754          | 1   |
| 0.3704        | 144.68 | 8500  | 0.6843          | 1   |
| 0.3625        | 153.19 | 9000  | 0.6707          | 1   |
| 0.356         | 161.7  | 9500  | 0.6812          | 1   |
| 0.3541        | 170.21 | 10000 | 0.6829          | 1   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "mounir4", "results": []}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

mounir4
=======


This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.6829
* Wer: 1


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: 1e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* training\_steps: 10000
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* training\_steps: 10000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* training\_steps: 10000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3