End of training

README.md

@@ -16,9 +16,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model was trained from scratch on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 4.9669
-- Cer: 0.7076
-- Wer: 0.9942
+- Loss: 4.0443
+- Cer: 0.5062
+- Wer: 0.8582
 
 ## Model description
 

all_results.json

@@ -0,0 +1,16 @@
+{
+    "epoch": 8.0,
+    "eval_cer": 0.5062452549582437,
+    "eval_loss": 4.04433012008667,
+    "eval_runtime": 157.4952,
+    "eval_samples": 3136,
+    "eval_samples_per_second": 19.912,
+    "eval_steps_per_second": 1.244,
+    "eval_wer": 0.85816470337969,
+    "total_flos": 3.0616960056652042e+19,
+    "train_loss": 4.665264035391807,
+    "train_runtime": 10255.3805,
+    "train_samples": 20000,
+    "train_samples_per_second": 15.602,
+    "train_steps_per_second": 0.488
+}

eval_results.json

@@ -0,0 +1,10 @@
+{
+    "epoch": 8.0,
+    "eval_cer": 0.5062452549582437,
+    "eval_loss": 4.04433012008667,
+    "eval_runtime": 157.4952,
+    "eval_samples": 3136,
+    "eval_samples_per_second": 19.912,
+    "eval_steps_per_second": 1.244,
+    "eval_wer": 0.85816470337969
+}

indicwav2vec_MUCS_warmup2000_s400shuff42_2129999.out

@@ -5562,3 +5562,67 @@ last prediction string लतद्वअनुवदआtमुmबकी औे
 
                                                 
 
 
                                                 
                                                     
+Printing predictions for a few samples:
+Sample 1:
+  Reference: लिबर ऑफिस impress में एक प्रस्तुति document बनाना और बुनियादी formatting के इस spoken tutorial में आपका स्वागत है
+######
+
+
+  Prediction: lिbरfpमेएकप्रस्तुडoयमentबननऔबुनयदfoरrmanकससपकnेंआपकं
+
+
+
+Sample 2:
+  Reference: इस tutorial में हम impress window के भागों के बारे में सीखेंगे और कैसे स्लाइड इन्सर्ट करें और कॉपी करें फॉन्ट तथा फॉन्ट को फॉर्मेट करना सीखेंगे
+######
+
+
+  Prediction: vविnडwकेागोंकेबारमें सीखेंऔरसde nसrकऔकरaकरनीें
+
+
+
+Sample 3:
+  Reference: यहाँ हम अपने ऑपरेटिंग सिस्टम के रूप में gnu/linux और लिबरऑफिस वर्जन 334 का उपयोग कर रहे हैं
+######
+
+
+  Prediction: याँम पनेऔपरेडिngसिस्t केरूमेंgनकऔरlिbऔfvर्जnकयगकं
+
+
+
+Sample 4:
+  Reference: चलिए अपनी प्रस्तुति प्रेजैटेशन sample impress open करते हैं जिसे पिछले tutorial में बनाया था
+######
+
+
+  Prediction: नीप्रस्तुanpजंं
+
+
+
+Sample 5:
+  Reference: चलिए देखते हैं कि screen पर क्या क्या है
+######
+
+
+  Prediction: येककक्रीnपरकयक्य
+
+
+
+last Reference string यह स्क्रिप्ट लता द्वारा अनुवादित है आईआईटी मुंबई की ओर से मैं रवि कुमार अब आपसे विदा लेता हूँहमसे जुड़ने के लिए धन्यवाद
+
+
+last prediction string दनदबकीऔमैंरविकुबजुडनेएन्यवाद
+{'eval_loss': 4.9668779373168945, 'eval_cer': 0.7076378272128795, 'eval_wer': 0.9942297976440556, 'eval_runtime': 159.4135, 'eval_samples_per_second': 19.672, 'eval_steps_per_second': 1.23, 'epoch': 8.0}
+{'train_runtime': 10255.3805, 'train_samples_per_second': 15.602, 'train_steps_per_second': 0.488, 'train_loss': 4.665264035391807, 'epoch': 8.0}
+***** train metrics *****
+  epoch                    =           8.0
+  total_flos               = 28514266066GF
+  train_loss               =        4.6653
+  train_runtime            =    2:50:55.38
+  train_samples            =         20000
+  train_samples_per_second =        15.602
+  train_steps_per_second   =         0.488
+08/21/2024 18:08:46 - INFO - __main__ - *** Evaluate ***
+/scratch/work/palp3/myenv/lib/python3.11/site-packages/transformers/models/wav2vec2/processing_wav2vec2.py:157: UserWarning: `as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your labels by using the argument `text` of the regular `__call__` method (either in the same call as your audio inputs, or in a separate call.
+  warnings.warn(
+
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train_results.json

@@ -0,0 +1,9 @@
+{
+    "epoch": 8.0,
+    "total_flos": 3.0616960056652042e+19,
+    "train_loss": 4.665264035391807,
+    "train_runtime": 10255.3805,
+    "train_samples": 20000,
+    "train_samples_per_second": 15.602,
+    "train_steps_per_second": 0.488
+}