Instructions to use thenlpresearcher/sequence_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use thenlpresearcher/sequence_classification with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("meta-llama/Meta-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "thenlpresearcher/sequence_classification") - Notebooks
- Google Colab
- Kaggle
| { | |
| "best_metric": 0.20379750430583954, | |
| "best_model_checkpoint": "sequence_classification/checkpoint-618", | |
| "epoch": 5.0, | |
| "eval_steps": 500, | |
| "global_step": 1030, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 1.0, | |
| "eval_loss": 0.2364644855260849, | |
| "eval_pearson": 0.9376906914778141, | |
| "eval_runtime": 33.6935, | |
| "eval_samples_per_second": 27.661, | |
| "eval_steps_per_second": 3.472, | |
| "step": 206 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "eval_loss": 0.21361978352069855, | |
| "eval_pearson": 0.9652459511637033, | |
| "eval_runtime": 33.666, | |
| "eval_samples_per_second": 27.684, | |
| "eval_steps_per_second": 3.475, | |
| "step": 412 | |
| }, | |
| { | |
| "epoch": 2.4271844660194173, | |
| "grad_norm": 0.9426701664924622, | |
| "learning_rate": 5.145631067961165e-05, | |
| "loss": 0.3209, | |
| "step": 500 | |
| }, | |
| { | |
| "epoch": 3.0, | |
| "eval_loss": 0.20379750430583954, | |
| "eval_pearson": 0.9631027995287645, | |
| "eval_runtime": 33.7681, | |
| "eval_samples_per_second": 27.6, | |
| "eval_steps_per_second": 3.465, | |
| "step": 618 | |
| }, | |
| { | |
| "epoch": 4.0, | |
| "eval_loss": 0.23791250586509705, | |
| "eval_pearson": 0.9668452710020821, | |
| "eval_runtime": 48.3963, | |
| "eval_samples_per_second": 19.258, | |
| "eval_steps_per_second": 2.418, | |
| "step": 824 | |
| }, | |
| { | |
| "epoch": 4.854368932038835, | |
| "grad_norm": 0.053257785737514496, | |
| "learning_rate": 2.912621359223301e-06, | |
| "loss": 0.0314, | |
| "step": 1000 | |
| }, | |
| { | |
| "epoch": 5.0, | |
| "eval_loss": 0.23692642152309418, | |
| "eval_pearson": 0.9678178837521502, | |
| "eval_runtime": 48.5841, | |
| "eval_samples_per_second": 19.183, | |
| "eval_steps_per_second": 2.408, | |
| "step": 1030 | |
| }, | |
| { | |
| "epoch": 5.0, | |
| "step": 1030, | |
| "total_flos": 5.610584124311962e+16, | |
| "train_loss": 0.17107450719741943, | |
| "train_runtime": 2510.3029, | |
| "train_samples_per_second": 13.076, | |
| "train_steps_per_second": 0.41 | |
| } | |
| ], | |
| "logging_steps": 500, | |
| "max_steps": 1030, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 5, | |
| "save_steps": 500, | |
| "stateful_callbacks": { | |
| "TrainerControl": { | |
| "args": { | |
| "should_epoch_stop": false, | |
| "should_evaluate": false, | |
| "should_log": false, | |
| "should_save": true, | |
| "should_training_stop": true | |
| }, | |
| "attributes": {} | |
| } | |
| }, | |
| "total_flos": 5.610584124311962e+16, | |
| "train_batch_size": 32, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |