Enpas
/

opus-base

Automatic Speech Recognition

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Enpas commited on Jun 25

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@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0224
-- Wer: 16.8793
 ## Model description
@@ -44,15 +44,15 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 500
-- training_steps: 1200
 - mixed_precision_training: Native AMP
 ### Training results
 | Training Loss | Epoch  | Step | Validation Loss | Wer     |
 |:-------------:|:------:|:----:|:---------------:|:-------:|
-| 0.0256        | 0.2201 | 600  | 0.0253          | 18.6784 |
-| 0.0251        | 0.4402 | 1200 | 0.0224          | 16.8793 |
 ### Framework versions

 This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on an unknown dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.0187
+- Wer: 15.8230
 ## Model description
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 500
+- training_steps: 2000
 - mixed_precision_training: Native AMP
 ### Training results
 | Training Loss | Epoch  | Step | Validation Loss | Wer     |
 |:-------------:|:------:|:----:|:---------------:|:-------:|
+| 0.0253        | 0.3668 | 1000 | 0.0209          | 16.5605 |
+| 0.0249        | 0.7337 | 2000 | 0.0187          | 15.8230 |
 ### Framework versions