Instructions to use SushantGautam/bert-large-cased_accuracy-coverage with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SushantGautam/bert-large-cased_accuracy-coverage with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SushantGautam/bert-large-cased_accuracy-coverage")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SushantGautam/bert-large-cased_accuracy-coverage") model = AutoModelForSequenceClassification.from_pretrained("SushantGautam/bert-large-cased_accuracy-coverage", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "best_metric": 0.03547798842191696, | |
| "best_model_checkpoint": "logs/google-bert/bert-large-cased_accuracy-coverage/checkpoint-1737", | |
| "epoch": 12.0, | |
| "eval_steps": 500, | |
| "global_step": 2316, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 1.0, | |
| "grad_norm": 18.177562713623047, | |
| "learning_rate": 1.900518134715026e-05, | |
| "loss": 0.0796, | |
| "step": 193 | |
| }, | |
| { | |
| "epoch": 1.0, | |
| "eval_MAE": 0.16079820692539215, | |
| "eval_R2": 0.09031999984589933, | |
| "eval_RMSE": 0.20937980711460114, | |
| "eval_loss": 0.04383990541100502, | |
| "eval_runtime": 14.15, | |
| "eval_samples_per_second": 203.604, | |
| "eval_steps_per_second": 3.463, | |
| "step": 193 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "grad_norm": 5.8847270011901855, | |
| "learning_rate": 1.800518134715026e-05, | |
| "loss": 0.0589, | |
| "step": 386 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "eval_MAE": 0.16792413592338562, | |
| "eval_R2": -0.035297909277749895, | |
| "eval_RMSE": 0.22336912155151367, | |
| "eval_loss": 0.04989376664161682, | |
| "eval_runtime": 14.0183, | |
| "eval_samples_per_second": 205.517, | |
| "eval_steps_per_second": 3.495, | |
| "step": 386 | |
| }, | |
| { | |
| "epoch": 3.0, | |
| "grad_norm": 7.614197731018066, | |
| "learning_rate": 1.7005181347150262e-05, | |
| "loss": 0.051, | |
| "step": 579 | |
| }, | |
| { | |
| "epoch": 3.0, | |
| "eval_MAE": 0.18675751984119415, | |
| "eval_R2": -0.032218313600698156, | |
| "eval_RMSE": 0.22303664684295654, | |
| "eval_loss": 0.0497453473508358, | |
| "eval_runtime": 14.1082, | |
| "eval_samples_per_second": 204.208, | |
| "eval_steps_per_second": 3.473, | |
| "step": 579 | |
| }, | |
| { | |
| "epoch": 4.0, | |
| "grad_norm": 0.26663488149642944, | |
| "learning_rate": 1.6005181347150262e-05, | |
| "loss": 0.0368, | |
| "step": 772 | |
| }, | |
| { | |
| "epoch": 4.0, | |
| "eval_MAE": 0.14720453321933746, | |
| "eval_R2": 0.17138686484945131, | |
| "eval_RMSE": 0.19983261823654175, | |
| "eval_loss": 0.03993307799100876, | |
| "eval_runtime": 13.9915, | |
| "eval_samples_per_second": 205.91, | |
| "eval_steps_per_second": 3.502, | |
| "step": 772 | |
| }, | |
| { | |
| "epoch": 5.0, | |
| "grad_norm": 2.195333480834961, | |
| "learning_rate": 1.500518134715026e-05, | |
| "loss": 0.0305, | |
| "step": 965 | |
| }, | |
| { | |
| "epoch": 5.0, | |
| "eval_MAE": 0.14292865991592407, | |
| "eval_R2": 0.23018361342873883, | |
| "eval_RMSE": 0.19261230528354645, | |
| "eval_loss": 0.037099506705999374, | |
| "eval_runtime": 14.2625, | |
| "eval_samples_per_second": 201.999, | |
| "eval_steps_per_second": 3.436, | |
| "step": 965 | |
| }, | |
| { | |
| "epoch": 6.0, | |
| "grad_norm": 4.641444683074951, | |
| "learning_rate": 1.400518134715026e-05, | |
| "loss": 0.0251, | |
| "step": 1158 | |
| }, | |
| { | |
| "epoch": 6.0, | |
| "eval_MAE": 0.14436666667461395, | |
| "eval_R2": 0.21001704033333712, | |
| "eval_RMSE": 0.19511890411376953, | |
| "eval_loss": 0.03807138651609421, | |
| "eval_runtime": 14.0937, | |
| "eval_samples_per_second": 204.418, | |
| "eval_steps_per_second": 3.477, | |
| "step": 1158 | |
| }, | |
| { | |
| "epoch": 7.0, | |
| "grad_norm": 6.497671127319336, | |
| "learning_rate": 1.300518134715026e-05, | |
| "loss": 0.0211, | |
| "step": 1351 | |
| }, | |
| { | |
| "epoch": 7.0, | |
| "eval_MAE": 0.14056500792503357, | |
| "eval_R2": 0.25886664349880983, | |
| "eval_RMSE": 0.18898992240428925, | |
| "eval_loss": 0.0357171930372715, | |
| "eval_runtime": 14.0545, | |
| "eval_samples_per_second": 204.987, | |
| "eval_steps_per_second": 3.486, | |
| "step": 1351 | |
| }, | |
| { | |
| "epoch": 8.0, | |
| "grad_norm": 7.818419933319092, | |
| "learning_rate": 1.2005181347150261e-05, | |
| "loss": 0.0174, | |
| "step": 1544 | |
| }, | |
| { | |
| "epoch": 8.0, | |
| "eval_MAE": 0.15229639410972595, | |
| "eval_R2": 0.11496506128758999, | |
| "eval_RMSE": 0.2065240740776062, | |
| "eval_loss": 0.0426521971821785, | |
| "eval_runtime": 14.1469, | |
| "eval_samples_per_second": 203.649, | |
| "eval_steps_per_second": 3.464, | |
| "step": 1544 | |
| }, | |
| { | |
| "epoch": 9.0, | |
| "grad_norm": 4.021462917327881, | |
| "learning_rate": 1.100518134715026e-05, | |
| "loss": 0.0153, | |
| "step": 1737 | |
| }, | |
| { | |
| "epoch": 9.0, | |
| "eval_MAE": 0.13968582451343536, | |
| "eval_R2": 0.2638301636372278, | |
| "eval_RMSE": 0.18835601210594177, | |
| "eval_loss": 0.03547798842191696, | |
| "eval_runtime": 14.0576, | |
| "eval_samples_per_second": 204.942, | |
| "eval_steps_per_second": 3.486, | |
| "step": 1737 | |
| }, | |
| { | |
| "epoch": 10.0, | |
| "grad_norm": 0.8230902552604675, | |
| "learning_rate": 1.0005181347150258e-05, | |
| "loss": 0.0127, | |
| "step": 1930 | |
| }, | |
| { | |
| "epoch": 10.0, | |
| "eval_MAE": 0.1468822956085205, | |
| "eval_R2": 0.2201558651457277, | |
| "eval_RMSE": 0.19386275112628937, | |
| "eval_loss": 0.037582769989967346, | |
| "eval_runtime": 14.0579, | |
| "eval_samples_per_second": 204.939, | |
| "eval_steps_per_second": 3.486, | |
| "step": 1930 | |
| }, | |
| { | |
| "epoch": 11.0, | |
| "grad_norm": 1.3326853513717651, | |
| "learning_rate": 9.005181347150261e-06, | |
| "loss": 0.0112, | |
| "step": 2123 | |
| }, | |
| { | |
| "epoch": 11.0, | |
| "eval_MAE": 0.15102224051952362, | |
| "eval_R2": 0.12659890818148722, | |
| "eval_RMSE": 0.2051621973514557, | |
| "eval_loss": 0.042091526091098785, | |
| "eval_runtime": 14.0985, | |
| "eval_samples_per_second": 204.348, | |
| "eval_steps_per_second": 3.476, | |
| "step": 2123 | |
| }, | |
| { | |
| "epoch": 12.0, | |
| "grad_norm": 4.036520481109619, | |
| "learning_rate": 8.005181347150259e-06, | |
| "loss": 0.0102, | |
| "step": 2316 | |
| }, | |
| { | |
| "epoch": 12.0, | |
| "eval_MAE": 0.15016663074493408, | |
| "eval_R2": 0.13732674296360936, | |
| "eval_RMSE": 0.20389831066131592, | |
| "eval_loss": 0.04157452657818794, | |
| "eval_runtime": 14.1218, | |
| "eval_samples_per_second": 204.011, | |
| "eval_steps_per_second": 3.47, | |
| "step": 2316 | |
| } | |
| ], | |
| "logging_steps": 500, | |
| "max_steps": 3860, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 20, | |
| "save_steps": 500, | |
| "total_flos": 1.2883969633724826e+17, | |
| "train_batch_size": 60, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |