Model description

More information needed

Intended uses & limitations

More information needed

More information needed

The following hyperparameters were used during training:

learning_rate: 1e-05
train_batch_size: 1
eval_batch_size: 2
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 2
total_train_batch_size: 16
total_eval_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 0.1
num_epochs: 5.0

Training Loss	Epoch	Step	Validation Loss
0.196	0.2778	25	0.1580
0.1687	0.5556	50	0.1145
0.0977	0.8333	75	0.1020
0.0687	1.1111	100	0.0979
0.0787	1.3889	125	0.0820
0.0445	1.6667	150	0.0824
0.0384	1.9444	175	0.0831
0.0309	2.2222	200	0.0793
0.0341	2.5	225	0.0758
0.035	2.7778	250	0.0759
0.0151	3.0556	275	0.0750
0.0211	3.3333	300	0.0756
0.019	3.6111	325	0.0743
0.0178	3.8889	350	0.0742
0.014	4.1667	375	0.0760
0.0102	4.4444	400	0.0784
0.0124	4.7222	425	0.0787
0.0104	5.0	450	0.0788