End of training

README.md

@@ -8,24 +8,9 @@ tags:
 - generated_from_trainer
 datasets:
 - mozilla-foundation/common_voice_11_0
-metrics:
-- wer
 model-index:
 - name: Whisper Small sv-SE augmented data tuned model
-  results:
-  - task:
-      name: Automatic Speech Recognition
-      type: automatic-speech-recognition
-    dataset:
-      name: Common Voice 11.0
-      type: mozilla-foundation/common_voice_11_0
-      config: sv-SE
-      split: test
-      args: 'config: sv-SE, split: test'
-    metrics:
-    - name: Wer
-      type: wer
-      value: 27.396413110698823
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -35,8 +20,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3705
-- Wer: 27.3964
+- eval_loss: 0.4671
+- eval_wer: 31.0882
+- eval_runtime: 2727.495
+- eval_samples_per_second: 1.858
+- eval_steps_per_second: 0.232
+- epoch: 1.3
+- step: 1000
 
 ## Model description
 
@@ -64,19 +54,9 @@ 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: 10
-- training_steps: 800
+- training_steps: 1600
 - mixed_precision_training: Native AMP
 
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Wer     |
-|:-------------:|:-----:|:----:|:---------------:|:-------:|
-| 0.7456        | 0.26  | 200  | 0.6935          | 45.3040 |
-| 0.6126        | 0.52  | 400  | 0.5469          | 37.3235 |
-| 0.5114        | 0.78  | 600  | 0.4381          | 31.7362 |
-| 0.1135        | 1.04  | 800  | 0.3705          | 27.3964 |
-
-
 ### Framework versions
 
 - Transformers 4.36.0.dev0

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