update model card README.md

README.md

@@ -1,12 +1,7 @@
 ---
 license: apache-2.0
 tags:
-- automatic-speech-recognition
-- google/fleurs
 - generated_from_trainer
-- hf-asr-leaderboard
-- ps
-- Pashto
 datasets:
 - fleurs
 metrics:
@@ -18,15 +13,15 @@ model-index:
       name: Automatic Speech Recognition
       type: automatic-speech-recognition
     dataset:
-      name: GOOGLE/FLEURS - PS_AF
+      name: fleurs
       type: fleurs
       config: ps_af
       split: test
-      args: 'Config: ps_af, Training split: train+validation, Eval split: test'
+      args: ps_af
     metrics:
     - name: Wer
       type: wer
-      value: 0.5137278308321964
+      value: 0.5156036834924966
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -34,11 +29,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 # facebook/wav2vec2-xls-r-300m
 
-This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the GOOGLE/FLEURS - PS_AF dataset.
+This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the fleurs dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.9154
-- Wer: 0.5137
-- Cer: 0.1966
+- Loss: 0.9162
+- Wer: 0.5156
+- Cer: 0.1969
 
 ## Model description
 
@@ -66,25 +61,26 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 2000
-- num_epochs: 50.0
+- training_steps: 4000
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
-|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
-| 5.0767        | 6.33  | 500  | 4.8783          | 1.0    | 1.0    |
-| 3.1156        | 12.66 | 1000 | 3.0990          | 1.0    | 1.0    |
-| 1.3506        | 18.99 | 1500 | 1.1056          | 0.7031 | 0.2889 |
-| 0.9997        | 25.32 | 2000 | 0.9191          | 0.5944 | 0.2301 |
-| 0.7838        | 31.65 | 2500 | 0.8952          | 0.5556 | 0.2152 |
-| 0.6665        | 37.97 | 3000 | 0.8908          | 0.5252 | 0.2017 |
-| 0.6265        | 44.3  | 3500 | 0.9063          | 0.5133 | 0.1954 |
+| Training Loss | Epoch | Step | Cer    | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:------:|:---------------:|:------:|
+| 5.0767        | 6.33  | 500  | 1.0    | 4.8783          | 1.0    |
+| 3.1156        | 12.66 | 1000 | 1.0    | 3.0990          | 1.0    |
+| 1.3506        | 18.99 | 1500 | 0.2889 | 1.1056          | 0.7031 |
+| 0.9997        | 25.32 | 2000 | 0.2301 | 0.9191          | 0.5944 |
+| 0.7838        | 31.65 | 2500 | 0.2152 | 0.8952          | 0.5556 |
+| 0.6665        | 37.97 | 3000 | 0.2017 | 0.8908          | 0.5252 |
+| 0.6265        | 44.3  | 3500 | 0.1954 | 0.9063          | 0.5133 |
+| 0.5935        | 50.63 | 4000 | 0.9162 | 0.5156          | 0.1969 |
 
 
 ### Framework versions
 
 - Transformers 4.26.0.dev0
-- Pytorch 1.13.0+cu117
+- Pytorch 1.13.1+cu117
 - Datasets 2.7.1.dev0
 - Tokenizers 0.13.2