End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Wer
       type: wer
-      value: 72.78630460448642
+      value: 0.6770956316410862
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,9 +32,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.9515
-- Wer Ortho: 72.7329
-- Wer: 72.7863
+- Loss: 0.7268
+- Wer Ortho: 0.6798
+- Wer: 0.6771
 
 ## Model description
 
@@ -60,21 +60,14 @@ 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
-- training_steps: 4000
+- training_steps: 500
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer     |
-|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
-| 0.0012        | 17.86  | 500  | 0.7266          | 67.7360   | 67.3554 |
-| 0.0002        | 35.71  | 1000 | 0.7895          | 74.0284   | 73.9079 |
-| 0.0001        | 53.57  | 1500 | 0.8302          | 74.9537   | 74.9115 |
-| 0.0001        | 71.43  | 2000 | 0.8608          | 75.2622   | 75.0885 |
-| 0.0           | 89.29  | 2500 | 0.8869          | 74.0284   | 73.9079 |
-| 0.0           | 107.14 | 3000 | 0.9105          | 73.9667   | 73.9079 |
-| 0.0           | 125.0  | 3500 | 0.9309          | 73.5965   | 73.5537 |
-| 0.0           | 142.86 | 4000 | 0.9515          | 72.7329   | 72.7863 |
+| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
+| 0.0014        | 17.86 | 500  | 0.7268          | 0.6798    | 0.6771 |
 
 
 ### Framework versions

model.safetensors

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training_args.bin

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