Instructions to use CodeIsAbstract/HybridModelScratch_ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CodeIsAbstract/HybridModelScratch_ with Transformers:
# Load model directly from transformers import HybridFourierLM model = HybridFourierLM.from_pretrained("CodeIsAbstract/HybridModelScratch_", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "best_global_step": null, | |
| "best_metric": null, | |
| "best_model_checkpoint": null, | |
| "epoch": 0.4, | |
| "eval_steps": 100, | |
| "global_step": 400, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 0.05, | |
| "grad_norm": 6.820826530456543, | |
| "learning_rate": 3.266666666666667e-05, | |
| "loss": 39.8282, | |
| "step": 50 | |
| }, | |
| { | |
| "epoch": 0.1, | |
| "grad_norm": 2.321176290512085, | |
| "learning_rate": 6.6e-05, | |
| "loss": 32.0977, | |
| "step": 100 | |
| }, | |
| { | |
| "epoch": 0.1, | |
| "eval_accuracy": 0.11411070917707537, | |
| "eval_loss": 7.302488327026367, | |
| "eval_runtime": 12.8861, | |
| "eval_samples_per_second": 75.275, | |
| "eval_steps_per_second": 4.734, | |
| "step": 100 | |
| }, | |
| { | |
| "epoch": 0.15, | |
| "grad_norm": 2.403538465499878, | |
| "learning_rate": 9.933333333333334e-05, | |
| "loss": 27.9639, | |
| "step": 150 | |
| }, | |
| { | |
| "epoch": 0.2, | |
| "grad_norm": 2.440488338470459, | |
| "learning_rate": 9.91822760447871e-05, | |
| "loss": 26.0238, | |
| "step": 200 | |
| }, | |
| { | |
| "epoch": 0.2, | |
| "eval_accuracy": 0.16184917453329808, | |
| "eval_loss": 6.333618640899658, | |
| "eval_runtime": 13.3491, | |
| "eval_samples_per_second": 72.664, | |
| "eval_steps_per_second": 4.57, | |
| "step": 200 | |
| }, | |
| { | |
| "epoch": 0.25, | |
| "grad_norm": 1.5482277870178223, | |
| "learning_rate": 9.669005017492143e-05, | |
| "loss": 25.0247, | |
| "step": 250 | |
| }, | |
| { | |
| "epoch": 0.3, | |
| "grad_norm": 3.2663464546203613, | |
| "learning_rate": 9.26078506448917e-05, | |
| "loss": 24.2338, | |
| "step": 300 | |
| }, | |
| { | |
| "epoch": 0.3, | |
| "eval_accuracy": 0.1829634890115987, | |
| "eval_loss": 5.955964088439941, | |
| "eval_runtime": 12.3645, | |
| "eval_samples_per_second": 78.45, | |
| "eval_steps_per_second": 4.933, | |
| "step": 300 | |
| }, | |
| { | |
| "epoch": 0.35, | |
| "grad_norm": 2.2301456928253174, | |
| "learning_rate": 8.707469186363446e-05, | |
| "loss": 23.716, | |
| "step": 350 | |
| }, | |
| { | |
| "epoch": 0.4, | |
| "grad_norm": 2.1302545070648193, | |
| "learning_rate": 8.027899891715287e-05, | |
| "loss": 23.2729, | |
| "step": 400 | |
| }, | |
| { | |
| "epoch": 0.4, | |
| "eval_accuracy": 0.1966725107382293, | |
| "eval_loss": 5.7180047035217285, | |
| "eval_runtime": 13.1479, | |
| "eval_samples_per_second": 73.776, | |
| "eval_steps_per_second": 4.64, | |
| "step": 400 | |
| } | |
| ], | |
| "logging_steps": 50, | |
| "max_steps": 1000, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 9223372036854775807, | |
| "save_steps": 200, | |
| "stateful_callbacks": { | |
| "TrainerControl": { | |
| "args": { | |
| "should_epoch_stop": false, | |
| "should_evaluate": false, | |
| "should_log": false, | |
| "should_save": true, | |
| "should_training_stop": false | |
| }, | |
| "attributes": {} | |
| } | |
| }, | |
| "total_flos": 6.69006654603264e+16, | |
| "train_batch_size": 64, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |