Model_name
stringclasses
2 values
Train_size
int64
50.8k
50.8k
Test_size
int64
12.7k
12.7k
arg
dict
lora
listlengths
4
7
Parameters
int64
1.55B
4.04B
Trainable_parameters
int64
8.43M
20.1M
r
int64
32
64
Memory Allocation
stringclasses
2 values
Training Time
stringclasses
2 values
accuracy
float64
0.91
0.91
f1_macro
float64
0.91
0.91
f1_weighted
float64
0.91
0.91
precision
float64
0.91
0.91
recall
float64
0.91
0.91
Alibaba-NLP/E2Rank-4B
50,775
12,652
{ "adafactor": false, "adam_beta1": 0.9, "adam_beta2": 0.999, "adam_epsilon": 1e-8, "bf16": false, "fp16": false, "fp16_opt_level": "O1", "gradient_accumulation_steps": 4, "half_precision_backend": "auto", "label_smoothing_factor": 0.2, "learning_rate": 0.00005, "lr_scheduler_type": "linear", "max_grad_norm": 1, "max_steps": -1, "n_gpu": 1, "num_train_epochs": 1, "optim": "adamw_8bit", "optim_args": "Not have", "per_device_eval_batch_size": 8, "per_device_train_batch_size": 8, "warmup_ratio": 0, "warmup_steps": 5, "weight_decay": 0.01 }
[ "down_proj", "gate_proj", "k_proj", "o_proj", "q_proj", "up_proj", "v_proj" ]
4,041,964,032
20,146,176
64
465.09
23459.81
0.913452
0.909783
0.913615
0.910713
0.909109
Qwen/Qwen2-1.5B
50,775
12,652
{ "adafactor": false, "adam_beta1": 0.9, "adam_beta2": 0.999, "adam_epsilon": 1e-8, "bf16": false, "fp16": false, "fp16_opt_level": "O1", "gradient_accumulation_steps": 4, "half_precision_backend": "auto", "label_smoothing_factor": 0.2, "learning_rate": 0.00005, "lr_scheduler_type": "linear", "max_grad_norm": 1, "max_steps": -1, "n_gpu": 1, "num_train_epochs": 1, "optim": "adamw_8bit", "optim_args": "Not have", "per_device_eval_batch_size": 8, "per_device_train_batch_size": 8, "warmup_ratio": 0, "warmup_steps": 5, "weight_decay": 0.01 }
[ "down_proj", "gate_proj", "o_proj", "up_proj" ]
1,551,718,400
8,429,568
32
239.75
8664.34
0.911318
0.907416
0.911483
0.908152
0.906923