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README.md

@@ -1,6 +1,6 @@
 ---
 language:
-- as
+- bn
 license: apache-2.0
 tags:
 - whisper-event
@@ -10,7 +10,7 @@ datasets:
 metrics:
 - wer
 model-index:
-- name: openai/whisper-large-v2-Assamese
+- name: openai/whisper-large-v2-Bengali
   results:
   - task:
       name: Automatic Speech Recognition
@@ -18,13 +18,13 @@ model-index:
     dataset:
       name: Common Voice 11.0
       type: mozilla-foundation/common_voice_11_0
-      config: as
+      config: bn
       split: test
-      args: as
+      args: bn
     metrics:
     - name: Wer
       type: wer
-      value: 58.13030138964086
+      value: None
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -34,8 +34,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the Common Voice 11.0 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.1469
-- Wer: 58.1303
+- Loss: None
+- Wer: None
 
 ## Model description
 
@@ -69,7 +69,7 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Wer     |
 |:-------------:|:-----:|:----:|:---------------:|:-------:|
-| 0.0646        | 1.13  | 600  | 1.1469          | 58.1303 |
+| 0.0646        | 1.13  | 600  | None            | None    |
 
 
 ### Framework versions