End of training

README.md

@@ -23,7 +23,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.8044064748201439
+      value: 0.8057553956834532
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -33,8 +33,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [openai/whisper-tiny.en](https://huggingface.co/openai/whisper-tiny.en) on the speech_commands dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.9815
-- Accuracy: 0.8044
+- Loss: 1.1281
+- Accuracy: 0.8058
 
 ## Model description
 
@@ -54,11 +54,11 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 96
-- eval_batch_size: 96
+- train_batch_size: 48
+- eval_batch_size: 48
 - seed: 42
 - gradient_accumulation_steps: 4
-- total_train_batch_size: 384
+- total_train_batch_size: 192
 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
@@ -69,9 +69,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.7314        | 1.0   | 103  | 1.1991          | 0.7968   |
-| 0.2414        | 2.0   | 206  | 0.9815          | 0.8044   |
-| 0.1419        | 3.0   | 309  | 0.9754          | 0.8040   |
+| 0.3022        | 1.0   | 206  | 1.1935          | 0.7972   |
+| 0.1455        | 2.0   | 412  | 1.1336          | 0.8008   |
+| 0.0752        | 3.0   | 618  | 1.1281          | 0.8058   |
 
 
 ### Framework versions

runs/Oct04_22-43-51_ki-g0008/events.out.tfevents.1759621205.ki-g0008.3679513.1

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+size 411