|
{ |
|
"best_metric": 0.6666666666666666, |
|
"best_model_checkpoint": "tiny-bert-sst2-distilled/run-28/checkpoint-160", |
|
"epoch": 2.0, |
|
"eval_steps": 500, |
|
"global_step": 320, |
|
"is_hyper_param_search": true, |
|
"is_local_process_zero": true, |
|
"is_world_process_zero": true, |
|
"log_history": [ |
|
{ |
|
"epoch": 1.0, |
|
"grad_norm": 1.9870704412460327, |
|
"learning_rate": 0.0006508102674737513, |
|
"loss": 0.5724, |
|
"step": 160 |
|
}, |
|
{ |
|
"epoch": 1.0, |
|
"eval_accuracy": 0.6666666666666666, |
|
"eval_f1": 0.0, |
|
"eval_loss": 0.5527419447898865, |
|
"eval_mcc": 0.0, |
|
"eval_precision": 0.0, |
|
"eval_recall": 0.0, |
|
"eval_runtime": 1.8742, |
|
"eval_samples_per_second": 680.285, |
|
"eval_steps_per_second": 21.342, |
|
"step": 160 |
|
}, |
|
{ |
|
"epoch": 2.0, |
|
"grad_norm": 2.1462595462799072, |
|
"learning_rate": 0.0005784980155322234, |
|
"loss": 0.5452, |
|
"step": 320 |
|
}, |
|
{ |
|
"epoch": 2.0, |
|
"eval_accuracy": 0.6533333333333333, |
|
"eval_f1": 0.42297650130548303, |
|
"eval_loss": 0.539912760257721, |
|
"eval_mcc": 0.18167801526026356, |
|
"eval_precision": 0.4750733137829912, |
|
"eval_recall": 0.3811764705882353, |
|
"eval_runtime": 2.2449, |
|
"eval_samples_per_second": 567.949, |
|
"eval_steps_per_second": 17.818, |
|
"step": 320 |
|
} |
|
], |
|
"logging_steps": 500, |
|
"max_steps": 1600, |
|
"num_input_tokens_seen": 0, |
|
"num_train_epochs": 10, |
|
"save_steps": 500, |
|
"total_flos": 583510875840.0, |
|
"train_batch_size": 32, |
|
"trial_name": null, |
|
"trial_params": { |
|
"alpha": 0.891982675867722, |
|
"learning_rate": 0.0007231225194152792, |
|
"num_train_epochs": 10, |
|
"temperature": 2 |
|
} |
|
} |
|
|