Training in progress, step 2000

model.safetensors

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runs/Oct20_21-52-43_MSI/events.out.tfevents.1760971968.MSI.20964.0

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runs/Oct20_22-31-22_MSI/events.out.tfevents.1760974284.MSI.21632.0

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test.py

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+import torch
+import librosa
+from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
+
+# ----------------------------
+# CONFIG
+# ----------------------------
+CHECKPOINT_PATH = "./wav2vec2-xlsr-khmer-300m/checkpoint-1800"
+AUDIO_PATH = "data\wavs\00000.wav"  # <-- change this to your test file
+
+# ----------------------------
+# LOAD MODEL AND PROCESSOR
+# ----------------------------
+print("Loading model and processor...")
+processor = Wav2Vec2Processor.from_pretrained(CHECKPOINT_PATH)
+model = Wav2Vec2ForCTC.from_pretrained(CHECKPOINT_PATH)
+model.eval()
+
+# ----------------------------
+# LOAD AUDIO
+# ----------------------------
+print("Loading audio:", AUDIO_PATH)
+speech, sr = librosa.load(AUDIO_PATH, sr=16000)
+inputs = processor(
+    speech,
+    sampling_rate=16000,
+    return_tensors="pt",
+    padding=True
+)
+
+with torch.no_grad():
+    logits = model(inputs.input_values).logits
+
+predicted_ids = torch.argmax(logits, dim=-1)
+transcription = processor.batch_decode(predicted_ids)[0]
+print("\n===============================")
+print("🔊 Transcription Result:")
+print(transcription)
+print("===============================")

training_args.bin

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