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: 2
eval_batch_size: 2
seed: 42
distributed_type: multi-GPU
num_devices: 7
total_train_batch_size: 14
total_eval_batch_size: 14
optimizer: Use OptimizerNames.ADAMW_TORCH 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: 0.05
num_epochs: 1.0

Training Loss	Epoch	Step	Validation Loss
0.0609	0.0777	1000	0.0622
0.0428	0.1553	2000	0.0455
0.04	0.2330	3000	0.0402
0.0349	0.3107	4000	0.0371
0.0384	0.3883	5000	0.0352
0.0319	0.4660	6000	0.0337
0.0313	0.5437	7000	0.0326
0.0312	0.6214	8000	0.0318
0.0307	0.6990	9000	0.0312
0.0303	0.7767	10000	0.0308
0.0283	0.8544	11000	0.0305
0.0279	0.9320	12000	0.0304