Add CER, hyperparameters, and training logs to README

README.md

@@ -9,6 +9,7 @@ datasets:
 - andrewbawitlung/mizonal-v3
 metrics:
 - wer
+- cer
 model-index:
 - name: whisper-medium-mizonal3-E2-lus-v2026.06
   results:
@@ -24,6 +25,9 @@ model-index:
     - name: Wer
       type: wer
       value: 21.7728
+    - name: Cer
+      type: cer
+      value: 7.3593
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -36,6 +40,7 @@ Note: ~1 hour of conversational speech was added to this dataset version.
 
 It achieves the following results on the evaluation set:
 - Wer: 21.7728
+- Cer: 7.3593
 
 ## Model description
 
@@ -66,4 +71,29 @@ More information needed
 
 ## Training procedure
 
+### Training hyperparameters
+
 More information needed
+
+### Training results
+
+| step | epoch | train_loss | eval_loss | eval_wer | eval_cer | learning_rate | grad_norm |
+| --- | --- | --- | --- | --- | --- | --- | --- |
+| 250 | 0.4553734061930783 | 0.6866 | 0.6109971404075623 | 0.34260971100515714 | 0.12720879276222788 | 0.0001494 | 7.834379196166992 |
+| 500 | 0.9107468123861566 | 0.8029 | 0.8720874786376953 | 0.6379293568161915 | 0.3605103194797851 | 0.00029939999999999996 | 20.601097106933594 |
+| 750 | 1.366120218579235 | 0.6327 | 0.7277008295059204 | 0.36489247834971295 | 0.1706071529544812 | 0.0002808067831449126 | 5.541914939880371 |
+| 1000 | 1.8214936247723132 | 0.4858 | 0.6909858584403992 | 0.34484771820570204 | 0.14426067288662708 | 0.00026153648509763614 | 3.856584310531616 |
+| 1250 | 2.276867030965392 | 0.3171 | 0.6292513608932495 | 0.3085530796925173 | 0.12282654792196777 | 0.00024226618705035967 | 3.361140251159668 |
+| 1500 | 2.73224043715847 | 0.264 | 0.6323882937431335 | 0.3075800330835847 | 0.11938083121289228 | 0.00022299588900308323 | 3.037963628768921 |
+| 1750 | 3.1876138433515484 | 0.1781 | 0.6203708052635193 | 0.3519509584509098 | 0.1572307039864292 | 0.00020372559095580676 | 2.4910476207733154 |
+| 2000 | 3.6429872495446265 | 0.1584 | 0.6050002574920654 | 0.2888975381920794 | 0.11347893695221939 | 0.0001844552929085303 | 2.562002658843994 |
+| 2250 | 4.098360655737705 | 0.0972 | 0.6101962924003601 | 0.2805293373552593 | 0.11922179813401187 | 0.00016518499486125384 | 1.7251062393188477 |
+| 2500 | 4.553734061930784 | 0.0894 | 0.5966487526893616 | 0.25338133696604065 | 0.09407690132880972 | 0.0001459146968139774 | 1.6773935556411743 |
+| 2750 | 5.009107468123862 | 0.0659 | 0.6184111833572388 | 0.24958645519120365 | 0.09423593440769014 | 0.00012664439876670092 | 0.9618287086486816 |
+| 3000 | 5.46448087431694 | 0.0524 | 0.6331346035003662 | 0.2560085628101586 | 0.10946776929601357 | 0.00010737410071942445 | 1.4324769973754883 |
+| 3250 | 5.919854280510018 | 0.0345 | 0.6023192405700684 | 0.23255813953488372 | 0.08416383941193102 | 8.810380267214798e-05 | 0.7218911647796631 |
+| 3500 | 6.375227686703097 | 0.0192 | 0.5783641934394836 | 0.24832149459959132 | 0.10796579021769862 | 6.883350462487152e-05 | 0.2467842400074005 |
+| 3750 | 6.830601092896175 | 0.0097 | 0.6010708808898926 | 0.2191300963316143 | 0.08168999151823579 | 4.956320657759506e-05 | 0.12510214745998383 |
+| 4000 | 7.285974499089253 | 0.0038 | 0.596376895904541 | 0.2028802179624404 | 0.07089341249646593 | 3.0292908530318598e-05 | 0.12478488683700562 |
+| 4250 | 7.741347905282332 | 0.002 | 0.6114839911460876 | 0.19976646881385618 | 0.06813683912920554 | 1.1022610483042137e-05 | 0.009769609197974205 |
+