The uploaded model is from epoch 4 with Matthews Correlation of 61.05

"best_metric": 0.4796141982078552,<br> "best_model_checkpoint": "/content/output_dir/checkpoint-268",<br> "epoch": 10.0,<br> "global_step": 2680,<br> "is_hyper_param_search": false,<br> "is_local_process_zero": true,<br> "is_world_process_zero": true,<br> "max_steps": 2680,<br> "num_train_epochs": 10,<br> "total_flos": 7113018526540800.0,<br> "trial_name": null,<br> "trial_params": null<br> <table class="table table-bordered table-hover table-condensed" style="width: 60%; overflow: auto"> <thead><tr><th title="Field #1">epoch</th> <th title="Field #2">eval_loss</th> <th title="Field #3">eval_matthews_correlation</th> <th title="Field #4">eval_runtime</th> <th title="Field #5">eval_samples_per_second</th> <th title="Field #6">eval_steps_per_second</th> <th title="Field #7">step</th> <th title="Field #8">learning_rate</th> <th title="Field #9">loss</th> </tr></thead> <tbody><tr> <td align="left">1</td> <td align="left">0.4796141982078552</td> <td align="left">0.5351033849356494</td> <td align="left">8.8067</td> <td align="left">118.433</td> <td align="left">14.875</td> <td align="left">268</td> <td align="left">0.000018067415730337083</td> <td align="left">0.4913</td> </tr> <tr> <td align="left">2</td> <td align="left">0.5334435701370239</td> <td align="left">0.5178799252679331</td> <td align="left">8.9439</td> <td align="left">116.616</td> <td align="left">14.647</td> <td align="left">536</td> <td align="left">0.00001605992509363296</td> <td align="left">0.2872</td> </tr> <tr> <td align="left">3</td> <td align="left">0.5544090270996094</td> <td align="left">0.5649788851042796</td> <td align="left">8.9467</td> <td align="left">116.58</td> <td align="left">14.642</td> <td align="left">804</td> <td align="left">0.000014052434456928841</td> <td align="left">0.1777</td> </tr> <tr> <td align="left">4</td> <td align="left">0.5754779577255249</td> <td align="left">0.6105374636148787</td> <td align="left">8.8982</td> <td align="left">117.215</td> <td align="left">14.722</td> <td align="left">1072</td> <td align="left">0.000012044943820224718</td> <td align="left">0.1263</td> </tr> <tr> <td align="left">5</td> <td align="left">0.7263916730880737</td> <td align="left">0.5807606001872874</td> <td align="left">8.9705</td> <td align="left">116.27</td> <td align="left">14.603</td> <td align="left">1340</td> <td align="left">0.000010037453183520601</td> <td align="left">0.0905</td> </tr> <tr> <td align="left">6</td> <td align="left">0.8121512532234192</td> <td align="left">0.5651092792103851</td> <td align="left">8.9924</td> <td align="left">115.987</td> <td align="left">14.568</td> <td align="left">1608</td> <td align="left">0.00000802996254681648</td> <td align="left">0.0692</td> </tr> <tr> <td align="left">7</td> <td align="left">0.941014289855957</td> <td align="left">0.5632084517291658</td> <td align="left">8.9583</td> <td align="left">116.428</td> <td align="left">14.623</td> <td align="left">1876</td> <td align="left">0.000006022471910112359</td> <td align="left">0.0413</td> </tr> <tr> <td align="left">8</td> <td align="left">1.0095174312591553</td> <td align="left">0.5856531698367675</td> <td align="left">9.0029</td> <td align="left">115.851</td> <td align="left">14.551</td> <td align="left">2144</td> <td align="left">0.00000401498127340824</td> <td align="left">0.0327</td> </tr> <tr> <td align="left">9</td> <td align="left">1.0425965785980225</td> <td align="left">0.5941395545037332</td> <td align="left">8.9217</td> <td align="left">116.906</td> <td align="left">14.683</td> <td align="left">2412</td> <td align="left">0.00000200749063670412</td> <td align="left">0.0202</td> </tr> <tr> <td align="left">10</td> <td align="left">1.0782166719436646</td> <td align="left">0.5956649094312695</td> <td align="left">8.9472</td> <td align="left">116.572</td> <td align="left">14.641</td> <td align="left">2680</td> <td align="left">0</td> <td align="left">0.0104</td> </tr> </tbody></table>