Instructions to use tarabukinivan/f23026ab-3731-43be-9da8-6a5f8535026a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tarabukinivan/f23026ab-3731-43be-9da8-6a5f8535026a with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/tinyllama") model = PeftModel.from_pretrained(base_model, "tarabukinivan/f23026ab-3731-43be-9da8-6a5f8535026a") - Notebooks
- Google Colab
- Kaggle
Invalid JSON:Unexpected token 'N', ..."al_loss": NaN,
"... is not valid JSON
| { | |
| "best_metric": null, | |
| "best_model_checkpoint": null, | |
| "epoch": 0.08379888268156424, | |
| "eval_steps": 8, | |
| "global_step": 30, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 0.002793296089385475, | |
| "eval_loss": NaN, | |
| "eval_runtime": 4.257, | |
| "eval_samples_per_second": 35.471, | |
| "eval_steps_per_second": 17.853, | |
| "step": 1 | |
| }, | |
| { | |
| "epoch": 0.008379888268156424, | |
| "grad_norm": NaN, | |
| "learning_rate": 6e-05, | |
| "loss": 0.0, | |
| "step": 3 | |
| }, | |
| { | |
| "epoch": 0.01675977653631285, | |
| "grad_norm": NaN, | |
| "learning_rate": 0.00012, | |
| "loss": 0.0, | |
| "step": 6 | |
| }, | |
| { | |
| "epoch": 0.0223463687150838, | |
| "eval_loss": NaN, | |
| "eval_runtime": 3.465, | |
| "eval_samples_per_second": 43.579, | |
| "eval_steps_per_second": 21.934, | |
| "step": 8 | |
| }, | |
| { | |
| "epoch": 0.025139664804469275, | |
| "grad_norm": NaN, | |
| "learning_rate": 0.00018, | |
| "loss": 0.0, | |
| "step": 9 | |
| }, | |
| { | |
| "epoch": 0.0335195530726257, | |
| "grad_norm": NaN, | |
| "learning_rate": 0.00019510565162951537, | |
| "loss": 0.0, | |
| "step": 12 | |
| }, | |
| { | |
| "epoch": 0.04189944134078212, | |
| "grad_norm": NaN, | |
| "learning_rate": 0.00017071067811865476, | |
| "loss": 0.0, | |
| "step": 15 | |
| }, | |
| { | |
| "epoch": 0.0446927374301676, | |
| "eval_loss": NaN, | |
| "eval_runtime": 3.4903, | |
| "eval_samples_per_second": 43.263, | |
| "eval_steps_per_second": 21.775, | |
| "step": 16 | |
| }, | |
| { | |
| "epoch": 0.05027932960893855, | |
| "grad_norm": NaN, | |
| "learning_rate": 0.00013090169943749476, | |
| "loss": 0.0, | |
| "step": 18 | |
| }, | |
| { | |
| "epoch": 0.05865921787709497, | |
| "grad_norm": NaN, | |
| "learning_rate": 8.435655349597689e-05, | |
| "loss": 0.0, | |
| "step": 21 | |
| }, | |
| { | |
| "epoch": 0.0670391061452514, | |
| "grad_norm": NaN, | |
| "learning_rate": 4.12214747707527e-05, | |
| "loss": 0.0, | |
| "step": 24 | |
| }, | |
| { | |
| "epoch": 0.0670391061452514, | |
| "eval_loss": NaN, | |
| "eval_runtime": 3.4981, | |
| "eval_samples_per_second": 43.167, | |
| "eval_steps_per_second": 21.726, | |
| "step": 24 | |
| }, | |
| { | |
| "epoch": 0.07541899441340782, | |
| "grad_norm": NaN, | |
| "learning_rate": 1.0899347581163221e-05, | |
| "loss": 0.0, | |
| "step": 27 | |
| }, | |
| { | |
| "epoch": 0.08379888268156424, | |
| "grad_norm": NaN, | |
| "learning_rate": 0.0, | |
| "loss": 0.0, | |
| "step": 30 | |
| } | |
| ], | |
| "logging_steps": 3, | |
| "max_steps": 30, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 1, | |
| "save_steps": 10, | |
| "stateful_callbacks": { | |
| "TrainerControl": { | |
| "args": { | |
| "should_epoch_stop": false, | |
| "should_evaluate": false, | |
| "should_log": false, | |
| "should_save": true, | |
| "should_training_stop": true | |
| }, | |
| "attributes": {} | |
| } | |
| }, | |
| "total_flos": 1544053158051840.0, | |
| "train_batch_size": 2, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |