Instructions to use tripathiarpan20/tuning-ab3318ee-d929-45d5-97e1-ccfee77df372 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tripathiarpan20/tuning-ab3318ee-d929-45d5-97e1-ccfee77df372 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Llama-3.2-1B-Instruct") model = PeftModel.from_pretrained(base_model, "tripathiarpan20/tuning-ab3318ee-d929-45d5-97e1-ccfee77df372") - Notebooks
- Google Colab
- Kaggle
| { | |
| "best_metric": null, | |
| "best_model_checkpoint": null, | |
| "epoch": 0.025789813023855575, | |
| "eval_steps": 3, | |
| "global_step": 10, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 0.0025789813023855577, | |
| "grad_norm": 1.1137349605560303, | |
| "learning_rate": 2e-05, | |
| "loss": 1.0005, | |
| "step": 1 | |
| }, | |
| { | |
| "epoch": 0.0025789813023855577, | |
| "eval_loss": 1.0008567571640015, | |
| "eval_runtime": 25.2563, | |
| "eval_samples_per_second": 6.493, | |
| "eval_steps_per_second": 3.247, | |
| "step": 1 | |
| }, | |
| { | |
| "epoch": 0.0051579626047711154, | |
| "grad_norm": 1.0478239059448242, | |
| "learning_rate": 4e-05, | |
| "loss": 0.9353, | |
| "step": 2 | |
| }, | |
| { | |
| "epoch": 0.007736943907156673, | |
| "grad_norm": 1.1948190927505493, | |
| "learning_rate": 6e-05, | |
| "loss": 0.9888, | |
| "step": 3 | |
| }, | |
| { | |
| "epoch": 0.007736943907156673, | |
| "eval_loss": 0.9943910837173462, | |
| "eval_runtime": 25.2196, | |
| "eval_samples_per_second": 6.503, | |
| "eval_steps_per_second": 3.251, | |
| "step": 3 | |
| }, | |
| { | |
| "epoch": 0.010315925209542231, | |
| "grad_norm": 0.9760572910308838, | |
| "learning_rate": 8e-05, | |
| "loss": 1.1157, | |
| "step": 4 | |
| }, | |
| { | |
| "epoch": 0.012894906511927788, | |
| "grad_norm": 0.713803768157959, | |
| "learning_rate": 0.0001, | |
| "loss": 0.8563, | |
| "step": 5 | |
| }, | |
| { | |
| "epoch": 0.015473887814313346, | |
| "grad_norm": 0.9101985692977905, | |
| "learning_rate": 0.00012, | |
| "loss": 0.8854, | |
| "step": 6 | |
| }, | |
| { | |
| "epoch": 0.015473887814313346, | |
| "eval_loss": 0.9519971609115601, | |
| "eval_runtime": 25.2384, | |
| "eval_samples_per_second": 6.498, | |
| "eval_steps_per_second": 3.249, | |
| "step": 6 | |
| }, | |
| { | |
| "epoch": 0.018052869116698903, | |
| "grad_norm": 0.8173288702964783, | |
| "learning_rate": 0.00014, | |
| "loss": 0.9227, | |
| "step": 7 | |
| }, | |
| { | |
| "epoch": 0.020631850419084462, | |
| "grad_norm": 0.7781127095222473, | |
| "learning_rate": 0.00016, | |
| "loss": 0.8288, | |
| "step": 8 | |
| }, | |
| { | |
| "epoch": 0.02321083172147002, | |
| "grad_norm": 0.607376217842102, | |
| "learning_rate": 0.00018, | |
| "loss": 0.9619, | |
| "step": 9 | |
| }, | |
| { | |
| "epoch": 0.02321083172147002, | |
| "eval_loss": 0.9006651639938354, | |
| "eval_runtime": 25.2807, | |
| "eval_samples_per_second": 6.487, | |
| "eval_steps_per_second": 3.244, | |
| "step": 9 | |
| }, | |
| { | |
| "epoch": 0.025789813023855575, | |
| "grad_norm": 0.6585434675216675, | |
| "learning_rate": 0.0002, | |
| "loss": 0.8898, | |
| "step": 10 | |
| } | |
| ], | |
| "logging_steps": 1, | |
| "max_steps": 10, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 1, | |
| "save_steps": 5, | |
| "stateful_callbacks": { | |
| "TrainerControl": { | |
| "args": { | |
| "should_epoch_stop": false, | |
| "should_evaluate": false, | |
| "should_log": false, | |
| "should_save": true, | |
| "should_training_stop": true | |
| }, | |
| "attributes": {} | |
| } | |
| }, | |
| "total_flos": 1935445139128320.0, | |
| "train_batch_size": 2, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |