
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# mounir2

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: 0.8560
- 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 3000
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:---:|
| 26.8537       | 0.42  | 100  | 25.5127         | 1   |
| 23.3042       | 0.85  | 200  | 20.5838         | 1   |
| 13.5844       | 1.27  | 300  | 10.8923         | 1   |
| 5.8285        | 1.7   | 400  | 4.5743          | 1   |
| 3.6732        | 2.12  | 500  | 3.4595          | 1   |
| 3.4969        | 2.55  | 600  | 3.3192          | 1   |
| 3.7275        | 2.97  | 700  | 3.2367          | 1   |
| 3.3092        | 3.4   | 800  | 3.1613          | 1   |
| 3.1658        | 3.82  | 900  | 3.1019          | 1   |
| 3.1157        | 4.25  | 1000 | 3.0578          | 1   |
| 3.105         | 4.67  | 1100 | 3.0208          | 1   |
| 3.0181        | 5.1   | 1200 | 2.9876          | 1   |
| 3.0154        | 5.52  | 1300 | 2.9543          | 1   |
| 2.9889        | 5.94  | 1400 | 2.9387          | 1   |
| 2.9461        | 6.37  | 1500 | 2.9246          | 1   |
| 2.9261        | 6.79  | 1600 | 2.9111          | 1   |
| 2.919         | 7.22  | 1700 | 2.9049          | 1   |
| 2.9235        | 7.64  | 1800 | 2.8974          | 1   |
| 2.899         | 8.07  | 1900 | 2.8864          | 1   |
| 2.9122        | 8.49  | 2000 | 2.8994          | 1   |
| 2.8856        | 8.92  | 2100 | 2.8789          | 1   |
| 2.8693        | 9.34  | 2200 | 2.8765          | 1   |
| 2.9063        | 9.77  | 2300 | 2.8693          | 1   |
| 2.8701        | 10.19 | 2400 | 2.8700          | 1   |
| 2.9013        | 10.62 | 2500 | 2.8647          | 1   |
| 2.8715        | 11.04 | 2600 | 2.8605          | 1   |
| 2.8524        | 11.46 | 2700 | 2.8706          | 1   |
| 2.8551        | 11.89 | 2800 | 2.8534          | 1   |
| 2.8466        | 12.31 | 2900 | 2.8517          | 1   |
| 2.8419        | 12.74 | 3000 | 2.8604          | 1   |
| 2.8345        | 13.16 | 3100 | 2.8388          | 1   |
| 2.827         | 13.59 | 3200 | 2.8220          | 1   |
| 2.6233        | 14.01 | 3300 | 2.5103          | 1   |
| 2.2908        | 14.44 | 3400 | 2.1460          | 1   |
| 1.9386        | 14.86 | 3500 | 1.7383          | 1   |
| 1.6341        | 15.29 | 3600 | 1.4527          | 1   |
| 1.5684        | 15.71 | 3700 | 1.2669          | 1   |
| 1.2713        | 16.14 | 3800 | 1.1512          | 1   |
| 1.1983        | 16.56 | 3900 | 1.0776          | 1   |
| 1.1806        | 16.99 | 4000 | 1.0261          | 1   |
| 1.1456        | 17.41 | 4100 | 0.9729          | 1   |
| 1.0942        | 17.83 | 4200 | 0.9407          | 1   |
| 1.0452        | 18.26 | 4300 | 0.9172          | 1   |
| 1.0082        | 18.68 | 4400 | 0.9006          | 1   |
| 0.9748        | 19.11 | 4500 | 0.8902          | 1   |
| 0.9672        | 19.53 | 4600 | 0.8742          | 1   |
| 0.9737        | 19.96 | 4700 | 0.8738          | 1   |
| 0.9567        | 20.38 | 4800 | 0.8639          | 1   |
| 0.988         | 20.81 | 4900 | 0.8565          | 1   |
| 0.9783        | 21.23 | 5000 | 0.8560          | 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": "mounir2", "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 

mounir2
=======


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: 0.8560
* 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: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 3000
* training\_steps: 5000
* 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: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 3000
* training\_steps: 5000
* 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: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 3000
* training\_steps: 5000
* 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