Sandiago21
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whisper-large-v2-greek

Automatic Speech Recognition

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Eval Results (legacy)

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Sandiago21 commited on Jul 18, 2023

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1 Parent(s): 9f9a448

update model card README.md

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@@ -23,7 +23,7 @@ model-index:
     metrics:
     - name: Wer
       type: wer
-      value: 0.19205164413960057
 ---
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -33,9 +33,9 @@ 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 FLEURS dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3106
-- Wer Ortho: 0.2256
-- Wer: 0.1921
 ## Model description
@@ -63,7 +63,7 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: constant_with_warmup
 - lr_scheduler_warmup_steps: 50
-- num_epochs: 12
 ### Training results
@@ -75,12 +75,7 @@ The following hyperparameters were used during training:
 | 0.0454        | 4.0   | 1099 | 0.2667          | 0.2315    | 0.1985 |
 | 0.028         | 5.0   | 1374 | 0.2579          | 0.2151    | 0.1822 |
 | 0.022         | 6.0   | 1649 | 0.2674          | 0.2188    | 0.1863 |
-| 0.0202        | 7.0   | 1924 | 0.2719          | 0.2140    | 0.1790 |
-| 0.0129        | 8.0   | 2199 | 0.2894          | 0.2219    | 0.1834 |
-| 0.0218        | 9.0   | 2473 | 0.2861          | 0.2180    | 0.1831 |
-| 0.0144        | 10.0  | 2748 | 0.3076          | 0.2211    | 0.1874 |
-| 0.0157        | 11.0  | 3023 | 0.3094          | 0.2264    | 0.1900 |
-| 0.0114        | 11.96 | 3288 | 0.3106          | 0.2256    | 0.1921 |
 ### Framework versions

     metrics:
     - name: Wer
       type: wer
+      value: 0.17739223993006523
 ---
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the FLEURS dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.2734
+- Wer Ortho: 0.2102
+- Wer: 0.1774
 ## Model description
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: constant_with_warmup
 - lr_scheduler_warmup_steps: 50
+- num_epochs: 7
 ### Training results
 | 0.0454        | 4.0   | 1099 | 0.2667          | 0.2315    | 0.1985 |
 | 0.028         | 5.0   | 1374 | 0.2579          | 0.2151    | 0.1822 |
 | 0.022         | 6.0   | 1649 | 0.2674          | 0.2188    | 0.1863 |
+| 0.0202        | 6.98  | 1918 | 0.2734          | 0.2102    | 0.1774 |
 ### Framework versions