update model card README.md

README.md

@@ -10,7 +10,7 @@ datasets:
 metrics:
 - wer
 model-index:
-- name: WhsprTiny-hi
+- name: WhpTiny-hi-v2
   results:
   - task:
       name: Automatic Speech Recognition
@@ -24,18 +24,18 @@ model-index:
     metrics:
     - name: Wer
       type: wer
-      value: 43.83526309755818
+      value: 43.666169895678095
 ---
 
 <!-- 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. -->
 
-# WhsprTiny-hi
+# WhpTiny-hi-v2
 
 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.9060
-- Wer: 43.8353
+- Loss: 1.0825
+- Wer: 43.6662
 
 ## Model description
 
@@ -58,9 +58,10 @@ The following hyperparameters were used during training:
 - train_batch_size: 16
 - eval_batch_size: 8
 - seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 400
 - training_steps: 5000
 - mixed_precision_training: Native AMP
 
@@ -68,11 +69,11 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Wer     |
 |:-------------:|:-----:|:----:|:---------------:|:-------:|
-| 0.2265        | 3.04  | 1000 | 0.5764          | 43.5028 |
-| 0.12          | 7.02  | 2000 | 0.6292          | 42.1271 |
-| 0.0375        | 10.05 | 3000 | 0.7510          | 43.5229 |
-| 0.0119        | 14.04 | 4000 | 0.8505          | 43.6203 |
-| 0.0094        | 18.02 | 5000 | 0.9060          | 43.8353 |
+| 0.1627        | 7.01  | 1000 | 0.5714          | 40.9378 |
+| 0.0275        | 14.02 | 2000 | 0.7620          | 42.5943 |
+| 0.0032        | 22.0  | 3000 | 0.9561          | 43.0443 |
+| 0.0012        | 29.01 | 4000 | 1.0517          | 43.4426 |
+| 0.0008        | 36.02 | 5000 | 1.0825          | 43.6662 |
 
 
 ### Framework versions