learning_rate: 5e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 8
total_train_batch_size: 256
total_eval_batch_size: 32
optimizer: Use OptimizerNames.PAGED_ADAMW with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.03
num_epochs: 3

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1497	0.3347	10	1.1414	0.5967
0.1812	0.6695	20	0.6084	0.73
0.2564	1.0335	30	0.4931	0.7933
0.1074	1.3682	40	0.6235	0.7433
0.102	1.7029	50	0.6734	0.8067
0.0859	2.0669	60	0.5501	0.8
0.0101	2.4017	70	1.7097	0.7767
0.0021	2.7364	80	1.8192	0.7833

Jennny/qwen25_7b_rm_eng_5e5_3ep

qwen25_7b_rm_eng_5e5_3ep