Update README.md

README.md

@@ -30,24 +30,29 @@ should probably proofread and complete it, then remove this comment. -->
 Wolof is a language spoken in Senegal and neighbouring countries, this language is not too well represented, there are few resources in the field of Text en speech
 In this sense we aim to bring our contribution to this, it is in this sense that enters this repo. 
 
-This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) , that is trained with the largest available speech dataset of the  [ALLFA project](https://github.com/besacier/ALFFA_PUBLIC/tree/master/ASR/WOLOF)
+This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) , that is trained with the largest available speech dataset of the  [ALFFA_PUBLIC project](https://github.com/besacier/ALFFA_PUBLIC/tree/master/ASR/WOLOF)
 
 It achieves the following results on the evaluation set:
 - Loss: 0.367826	
 - Wer: 0.212565
 
 ## Model description
-More information needed
-## Intended uses & limitations
-More information needed
+The duration of the training data is 16.8 hours, which we have divided into 10,000 audio files for the training and 3,339 for the test.
 ## Training and evaluation data
-More information needed
-## Training procedure
+We eval the model at every 1500 step , and log it .  and save at every 33340 step
 ### Training hyperparameters
-More information needed
-### Training results
+The following hyperparameters were used during training:
+- learning_rate: 1e-4
+- train_batch_size: 3
+- eval_batch_size : 8
+- total_train_batch_size: 64
+- total_eval_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 1000
+- num_epochs: 10.0
 
- 
+### Training results
 
 | Step    | Training Loss | Validation Loss | Wer    |
 |:-------:|:-------------:|:---------------:|:------:|