Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.7417	0.5435	25	0.5925	{'accuracy': 0.8695652173913043}	0.8089	0.7561	0.8696
0.7226	1.0870	50	0.6167	{'accuracy': 0.8695652173913043}	0.8089	0.7561	0.8696
0.5606	1.6304	75	0.6808	{'accuracy': 0.8695652173913043}	0.8089	0.7561	0.8696
0.8858	2.1739	100	0.5850	{'accuracy': 0.8695652173913043}	0.8089	0.7561	0.8696
0.6573	2.7174	125	0.5968	{'accuracy': 0.8695652173913043}	0.8089	0.7561	0.8696
0.7942	3.2609	150	0.6142	{'accuracy': 0.8695652173913043}	0.8089	0.7561	0.8696
0.7497	3.8043	175	0.5915	{'accuracy': 0.8695652173913043}	0.8089	0.7561	0.8696
0.7408	4.3478	200	0.5899	{'accuracy': 0.8695652173913043}	0.8089	0.7561	0.8696
0.6499	4.8913	225	0.5989	{'accuracy': 0.8695652173913043}	0.8089	0.7561	0.8696
0.6725	5.4348	250	0.5865	{'accuracy': 0.8695652173913043}	0.8089	0.7561	0.8696
0.6797	5.9783	275	0.5852	{'accuracy': 0.8695652173913043}	0.8089	0.7561	0.8696
0.6553	6.5217	300	0.5861	{'accuracy': 0.8695652173913043}	0.8089	0.7561	0.8696
0.6535	7.0652	325	0.5863	{'accuracy': 0.8695652173913043}	0.8089	0.7561	0.8696
0.7297	7.6087	350	0.5865	{'accuracy': 0.8695652173913043}	0.8089	0.7561	0.8696

qiaoen04/distilhubert-finetuned-babycry-v7

distilhubert-finetuned-babycry-v7