Model save

README.md

@@ -4,7 +4,7 @@ base_model: openai/whisper-large-v3
 tags:
 - generated_from_trainer
 datasets:
-- fsicoli/common_voice_18_0
+- common_voice_18_0
 metrics:
 - wer
 model-index:
@@ -14,15 +14,15 @@ model-index:
       name: Automatic Speech Recognition
       type: automatic-speech-recognition
     dataset:
-      name: fsicoli/common_voice_18_0 pt
-      type: fsicoli/common_voice_18_0
+      name: common_voice_18_0
+      type: common_voice_18_0
       config: pt
       split: None
       args: pt
     metrics:
     - name: Wer
       type: wer
-      value: 0.10174567584881486
+      value: 0.10366752081998719
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -30,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # whisper-large-v3-pt-3000h-3
 
-This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the fsicoli/common_voice_18_0 pt dataset.
+This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the common_voice_18_0 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1478
-- Wer: 0.1017
+- Loss: 0.1486
+- Wer: 0.1037
 
 ## Model description
 
@@ -69,7 +69,6 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch  | Step | Validation Loss | Wer    |
 |:-------------:|:------:|:----:|:---------------:|:------:|
 | 0.13          | 0.9998 | 691  | 0.1486          | 0.1037 |
-| 0.0844        | 1.9998 | 1382 | 0.1478          | 0.1017 |
 
 
 ### Framework versions

runs/Aug20_09-28-11_DITEC2014063010/events.out.tfevents.1724157185.DITEC2014063010.25420.0

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+size 6100

training_args.bin

@@ -1,3 +1,3 @@
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 size 5368