End of training

README.md

@@ -23,7 +23,7 @@ model-index:
     metrics:
     - name: Wer
       type: wer
-      value: 44.34103491130946
+      value: 44.99209128911987
 ---
 
 <!-- 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 [imTak/whisper_large_v3_ko_ft_ft](https://huggingface.co/imTak/whisper_large_v3_ko_ft_ft) on the Economy dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6659
-- Wer: 44.3410
+- Loss: 0.7148
+- Wer: 44.9921
 
 ## Model description
 
@@ -54,13 +54,13 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 1e-05
-- train_batch_size: 16
-- eval_batch_size: 16
+- train_batch_size: 32
+- eval_batch_size: 32
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 500
-- training_steps: 4000
+- training_steps: 8000
 - mixed_precision_training: Native AMP
 
 ### Training results
@@ -71,6 +71,10 @@ The following hyperparameters were used during training:
 | 0.7497        | 0.9259 | 2000 | 0.7351          | 47.6006 |
 | 0.4979        | 1.3889 | 3000 | 0.6992          | 45.6375 |
 | 0.5197        | 1.8519 | 4000 | 0.6659          | 44.3410 |
+| 0.4264        | 2.3148 | 5000 | 0.7168          | 46.6459 |
+| 0.3911        | 2.7778 | 6000 | 0.6988          | 45.0726 |
+| 0.2565        | 3.2407 | 7000 | 0.7203          | 44.8000 |
+| 0.2462        | 3.7037 | 8000 | 0.7148          | 44.9921 |
 
 
 ### Framework versions

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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+oid sha256:3039fc08064e23dcfafa5606e397d782f6b937e5de42810f4dde77922d8e1b06
 size 3235581408