Update README.md

README.md

@@ -8,7 +8,11 @@ library_name: peft
 license: apache-2.0
 metrics:
 - wer
+- ter
+- chrf
+- cer
 - bleu
+- suber
 tags:
 - generated_from_trainer
 model-index:
@@ -25,11 +29,24 @@ model-index:
       args: 'config: th, split: validation'
     metrics:
     - type: wer
-      value: 0.8100890207715133
+      value: 0.8101
       name: Wer
+    - name: Ter
+      type: ter
+      value: 81.0089
+    - name: ChrF
+      type: chrf
+      value: 87.4811
+    - name: CER
+      type: cer
+      value: 0.1041
     - type: bleu
-      value: 8.739138222980559
+      value: 8.7391
       name: Bleu
+    - name: SubER
+      type: suber
+      value: 0.8189
+pipeline_tag: automatic-speech-recognition
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -41,25 +58,11 @@ This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingf
 It achieves the following results on the evaluation set:
 - Loss: 0.1894
 - Wer: 0.8101
-- Ter: {'score': 81.00890207715133, 'num_edits': 546, 'ref_length': 674.0}
-- Chrf: {'score': 87.48106146298329, 'char_order': 6, 'word_order': 0, 'beta': 2}
+- Ter: 81.0089
+- Chrf: 87.4811
 - Cer: 0.1041
 - Bleu: 8.7391
-- Average Suber: 0.8189
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
+- SubER: 0.8189
 
 ### Training hyperparameters
 
@@ -78,11 +81,11 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Wer    | Ter                                                                 | Chrf                                                                      | Cer    | Bleu   | Average Suber |
-|:-------------:|:-----:|:----:|:---------------:|:------:|:-------------------------------------------------------------------:|:-------------------------------------------------------------------------:|:------:|:------:|:-------------:|
-| 0.3053        | 0.32  | 50   | 0.2052          | 0.8457 | {'score': 84.56973293768546, 'num_edits': 570, 'ref_length': 674.0} | {'score': 86.69717825036054, 'char_order': 6, 'word_order': 0, 'beta': 2} | 0.1115 | 7.8703 | 0.8640        |
-| 0.3752        | 0.64  | 100  | 0.1937          | 0.8323 | {'score': 83.23442136498517, 'num_edits': 561, 'ref_length': 674.0} | {'score': 86.98005540895491, 'char_order': 6, 'word_order': 0, 'beta': 2} | 0.1087 | 8.1510 | 0.8469        |
-| 0.2794        | 0.96  | 150  | 0.1894          | 0.8101 | {'score': 81.00890207715133, 'num_edits': 546, 'ref_length': 674.0} | {'score': 87.48106146298329, 'char_order': 6, 'word_order': 0, 'beta': 2} | 0.1041 | 8.7391 | 0.8189        |
+| Training Loss | Epoch | Step | Validation Loss | Wer    | Ter     | Chrf    | Cer    | Bleu   |   SubER   |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:-------:|:------:|:------:|:---------:|
+| 0.3053        | 0.32  | 50   | 0.2052          | 0.8457 | 84.5697 | 86.6971 | 0.1115 | 7.8703 | 0.8640    |
+| 0.3752        | 0.64  | 100  | 0.1937          | 0.8323 | 83.2344 | 86.9801 | 0.1087 | 8.1510 | 0.8469    |
+| 0.2794        | 0.96  | 150  | 0.1894          | 0.8101 | 81.0089 | 87.4811 | 0.1041 | 8.7391 | 0.8189    |
 
 
 ### Framework versions