Jzuluaga's picture
updating the repo with the fine-tuned model
a9b258a
raw
history blame
5.29 kB
{
"best_metric": null,
"best_model_checkpoint": null,
"epoch": 20.13422818791946,
"global_step": 3000,
"is_hyper_param_search": false,
"is_local_process_zero": true,
"is_world_process_zero": true,
"log_history": [
{
"epoch": 3.36,
"eval_accuracy": 0.9206798866855525,
"eval_f1": 0.9303482587064678,
"eval_loss": 0.2345595508813858,
"eval_precision": 0.919672131147541,
"eval_recall": 0.9412751677852349,
"eval_report": " precision recall f1-score support\n\n 0 0.92 0.89 0.91 463\n 1 0.92 0.94 0.93 596\n\n accuracy 0.92 1059\n macro avg 0.92 0.92 0.92 1059\nweighted avg 0.92 0.92 0.92 1059\n",
"eval_runtime": 8.0364,
"eval_samples_per_second": 131.775,
"eval_steps_per_second": 8.337,
"step": 500
},
{
"epoch": 6.71,
"learning_rate": 4e-05,
"loss": 0.2212,
"step": 1000
},
{
"epoch": 6.71,
"eval_accuracy": 0.9046270066100094,
"eval_f1": 0.9141886151231945,
"eval_loss": 0.31608325242996216,
"eval_precision": 0.9259896729776248,
"eval_recall": 0.9026845637583892,
"eval_report": " precision recall f1-score support\n\n 0 0.88 0.91 0.89 463\n 1 0.93 0.90 0.91 596\n\n accuracy 0.90 1059\n macro avg 0.90 0.90 0.90 1059\nweighted avg 0.91 0.90 0.90 1059\n",
"eval_runtime": 8.0054,
"eval_samples_per_second": 132.285,
"eval_steps_per_second": 8.369,
"step": 1000
},
{
"epoch": 10.07,
"eval_accuracy": 0.9065155807365439,
"eval_f1": 0.9167367535744324,
"eval_loss": 0.43374723196029663,
"eval_precision": 0.9190556492411467,
"eval_recall": 0.9144295302013423,
"eval_report": " precision recall f1-score support\n\n 0 0.89 0.90 0.89 463\n 1 0.92 0.91 0.92 596\n\n accuracy 0.91 1059\n macro avg 0.90 0.91 0.91 1059\nweighted avg 0.91 0.91 0.91 1059\n",
"eval_runtime": 8.0154,
"eval_samples_per_second": 132.12,
"eval_steps_per_second": 8.359,
"step": 1500
},
{
"epoch": 13.42,
"learning_rate": 2e-05,
"loss": 0.0651,
"step": 2000
},
{
"epoch": 13.42,
"eval_accuracy": 0.9178470254957507,
"eval_f1": 0.9271966527196652,
"eval_loss": 0.47431105375289917,
"eval_precision": 0.9248747913188647,
"eval_recall": 0.9295302013422819,
"eval_report": " precision recall f1-score support\n\n 0 0.91 0.90 0.91 463\n 1 0.92 0.93 0.93 596\n\n accuracy 0.92 1059\n macro avg 0.92 0.92 0.92 1059\nweighted avg 0.92 0.92 0.92 1059\n",
"eval_runtime": 8.0135,
"eval_samples_per_second": 132.152,
"eval_steps_per_second": 8.361,
"step": 2000
},
{
"epoch": 16.78,
"eval_accuracy": 0.9102927289896129,
"eval_f1": 0.9203688181056161,
"eval_loss": 0.5537705421447754,
"eval_precision": 0.9195979899497487,
"eval_recall": 0.9211409395973155,
"eval_report": " precision recall f1-score support\n\n 0 0.90 0.90 0.90 463\n 1 0.92 0.92 0.92 596\n\n accuracy 0.91 1059\n macro avg 0.91 0.91 0.91 1059\nweighted avg 0.91 0.91 0.91 1059\n",
"eval_runtime": 8.0263,
"eval_samples_per_second": 131.941,
"eval_steps_per_second": 8.348,
"step": 2500
},
{
"epoch": 20.13,
"learning_rate": 0.0,
"loss": 0.0296,
"step": 3000
},
{
"epoch": 20.13,
"eval_accuracy": 0.9102927289896129,
"eval_f1": 0.9199663016006739,
"eval_loss": 0.6190621256828308,
"eval_precision": 0.9238578680203046,
"eval_recall": 0.9161073825503355,
"eval_report": " precision recall f1-score support\n\n 0 0.89 0.90 0.90 463\n 1 0.92 0.92 0.92 596\n\n accuracy 0.91 1059\n macro avg 0.91 0.91 0.91 1059\nweighted avg 0.91 0.91 0.91 1059\n",
"eval_runtime": 8.0249,
"eval_samples_per_second": 131.965,
"eval_steps_per_second": 8.349,
"step": 3000
},
{
"epoch": 20.13,
"step": 3000,
"total_flos": 5.04436515336192e+16,
"train_loss": 0.10527635129292806,
"train_runtime": 3964.4436,
"train_samples_per_second": 48.431,
"train_steps_per_second": 0.757
}
],
"max_steps": 3000,
"num_train_epochs": 21,
"total_flos": 5.04436515336192e+16,
"trial_name": null,
"trial_params": null
}