Instructions to use annnettte/lettucedect-tool-calling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use annnettte/lettucedect-tool-calling with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="annnettte/lettucedect-tool-calling")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("annnettte/lettucedect-tool-calling") model = AutoModelForTokenClassification.from_pretrained("annnettte/lettucedect-tool-calling") - Notebooks
- Google Colab
- Kaggle
| { | |
| "best_global_step": 525, | |
| "best_metric": 0.8338557993730408, | |
| "best_model_checkpoint": "./lettuce_ft/checkpoint-525", | |
| "epoch": 5.0, | |
| "eval_steps": 500, | |
| "global_step": 525, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 0.19047619047619047, | |
| "grad_norm": 0.7677925825119019, | |
| "learning_rate": 7.600000000000001e-06, | |
| "loss": 0.19512724876403809, | |
| "step": 20 | |
| }, | |
| { | |
| "epoch": 0.38095238095238093, | |
| "grad_norm": 0.23630067706108093, | |
| "learning_rate": 1.5600000000000003e-05, | |
| "loss": 0.15847638845443726, | |
| "step": 40 | |
| }, | |
| { | |
| "epoch": 0.5714285714285714, | |
| "grad_norm": 0.6374622583389282, | |
| "learning_rate": 1.9689655172413796e-05, | |
| "loss": 0.20727028846740722, | |
| "step": 60 | |
| }, | |
| { | |
| "epoch": 0.7619047619047619, | |
| "grad_norm": 0.8266599178314209, | |
| "learning_rate": 1.9e-05, | |
| "loss": 0.18287111520767213, | |
| "step": 80 | |
| }, | |
| { | |
| "epoch": 0.9523809523809523, | |
| "grad_norm": 0.6583699584007263, | |
| "learning_rate": 1.831034482758621e-05, | |
| "loss": 0.12251497507095337, | |
| "step": 100 | |
| }, | |
| { | |
| "epoch": 1.0, | |
| "eval_f1": 0.7323615160349854, | |
| "eval_loss": 0.11771774291992188, | |
| "eval_precision": 0.988976377952756, | |
| "eval_recall": 0.5814814814814815, | |
| "eval_runtime": 20.0131, | |
| "eval_samples_per_second": 8.994, | |
| "eval_steps_per_second": 2.249, | |
| "step": 105 | |
| }, | |
| { | |
| "epoch": 1.1428571428571428, | |
| "grad_norm": 0.5870521664619446, | |
| "learning_rate": 1.7620689655172414e-05, | |
| "loss": 0.12844752073287963, | |
| "step": 120 | |
| }, | |
| { | |
| "epoch": 1.3333333333333333, | |
| "grad_norm": 1.8096352815628052, | |
| "learning_rate": 1.6931034482758623e-05, | |
| "loss": 0.14761706590652465, | |
| "step": 140 | |
| }, | |
| { | |
| "epoch": 1.5238095238095237, | |
| "grad_norm": 0.42143744230270386, | |
| "learning_rate": 1.6241379310344828e-05, | |
| "loss": 0.10572866201400757, | |
| "step": 160 | |
| }, | |
| { | |
| "epoch": 1.7142857142857144, | |
| "grad_norm": 1.1219831705093384, | |
| "learning_rate": 1.5551724137931036e-05, | |
| "loss": 0.08384537696838379, | |
| "step": 180 | |
| }, | |
| { | |
| "epoch": 1.9047619047619047, | |
| "grad_norm": 0.8192638158798218, | |
| "learning_rate": 1.4862068965517243e-05, | |
| "loss": 0.1669264554977417, | |
| "step": 200 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "eval_f1": 0.7592997811816192, | |
| "eval_loss": 0.09724947810173035, | |
| "eval_precision": 0.9278074866310161, | |
| "eval_recall": 0.6425925925925926, | |
| "eval_runtime": 19.9967, | |
| "eval_samples_per_second": 9.001, | |
| "eval_steps_per_second": 2.25, | |
| "step": 210 | |
| }, | |
| { | |
| "epoch": 2.0952380952380953, | |
| "grad_norm": 0.6344627141952515, | |
| "learning_rate": 1.417241379310345e-05, | |
| "loss": 0.08497620224952698, | |
| "step": 220 | |
| }, | |
| { | |
| "epoch": 2.2857142857142856, | |
| "grad_norm": 0.5775904655456543, | |
| "learning_rate": 1.3482758620689656e-05, | |
| "loss": 0.08870592713356018, | |
| "step": 240 | |
| }, | |
| { | |
| "epoch": 2.4761904761904763, | |
| "grad_norm": 0.49520859122276306, | |
| "learning_rate": 1.2793103448275863e-05, | |
| "loss": 0.08883096575737, | |
| "step": 260 | |
| }, | |
| { | |
| "epoch": 2.6666666666666665, | |
| "grad_norm": 1.1992110013961792, | |
| "learning_rate": 1.2103448275862071e-05, | |
| "loss": 0.08080946207046509, | |
| "step": 280 | |
| }, | |
| { | |
| "epoch": 2.857142857142857, | |
| "grad_norm": 1.4169745445251465, | |
| "learning_rate": 1.1413793103448276e-05, | |
| "loss": 0.07005050182342529, | |
| "step": 300 | |
| }, | |
| { | |
| "epoch": 3.0, | |
| "eval_f1": 0.8050982474774296, | |
| "eval_loss": 0.08078155666589737, | |
| "eval_precision": 0.9439601494396015, | |
| "eval_recall": 0.7018518518518518, | |
| "eval_runtime": 20.0961, | |
| "eval_samples_per_second": 8.957, | |
| "eval_steps_per_second": 2.239, | |
| "step": 315 | |
| }, | |
| { | |
| "epoch": 3.0476190476190474, | |
| "grad_norm": 0.8966546058654785, | |
| "learning_rate": 1.0724137931034484e-05, | |
| "loss": 0.06641889810562134, | |
| "step": 320 | |
| }, | |
| { | |
| "epoch": 3.238095238095238, | |
| "grad_norm": 0.5824030041694641, | |
| "learning_rate": 1.003448275862069e-05, | |
| "loss": 0.05119739174842834, | |
| "step": 340 | |
| }, | |
| { | |
| "epoch": 3.4285714285714284, | |
| "grad_norm": 0.6942387223243713, | |
| "learning_rate": 9.344827586206898e-06, | |
| "loss": 0.04003562927246094, | |
| "step": 360 | |
| }, | |
| { | |
| "epoch": 3.619047619047619, | |
| "grad_norm": 0.5906447172164917, | |
| "learning_rate": 8.655172413793104e-06, | |
| "loss": 0.04091911017894745, | |
| "step": 380 | |
| }, | |
| { | |
| "epoch": 3.8095238095238093, | |
| "grad_norm": 0.3436790704727173, | |
| "learning_rate": 7.965517241379311e-06, | |
| "loss": 0.04960331916809082, | |
| "step": 400 | |
| }, | |
| { | |
| "epoch": 4.0, | |
| "grad_norm": 0.3449792265892029, | |
| "learning_rate": 7.275862068965518e-06, | |
| "loss": 0.03436199724674225, | |
| "step": 420 | |
| }, | |
| { | |
| "epoch": 4.0, | |
| "eval_f1": 0.8254963427377221, | |
| "eval_loss": 0.07085700333118439, | |
| "eval_precision": 0.947242206235012, | |
| "eval_recall": 0.7314814814814815, | |
| "eval_runtime": 20.0966, | |
| "eval_samples_per_second": 8.957, | |
| "eval_steps_per_second": 2.239, | |
| "step": 420 | |
| }, | |
| { | |
| "epoch": 4.190476190476191, | |
| "grad_norm": 0.511233389377594, | |
| "learning_rate": 6.586206896551724e-06, | |
| "loss": 0.03371661007404327, | |
| "step": 440 | |
| }, | |
| { | |
| "epoch": 4.380952380952381, | |
| "grad_norm": 0.4449719786643982, | |
| "learning_rate": 5.896551724137931e-06, | |
| "loss": 0.0406580239534378, | |
| "step": 460 | |
| }, | |
| { | |
| "epoch": 4.571428571428571, | |
| "grad_norm": 0.3001626133918762, | |
| "learning_rate": 5.206896551724139e-06, | |
| "loss": 0.025170013308525085, | |
| "step": 480 | |
| }, | |
| { | |
| "epoch": 4.761904761904762, | |
| "grad_norm": 0.4409080743789673, | |
| "learning_rate": 4.517241379310345e-06, | |
| "loss": 0.03046942949295044, | |
| "step": 500 | |
| }, | |
| { | |
| "epoch": 4.9523809523809526, | |
| "grad_norm": 0.1583988219499588, | |
| "learning_rate": 3.827586206896552e-06, | |
| "loss": 0.020532441139221192, | |
| "step": 520 | |
| }, | |
| { | |
| "epoch": 5.0, | |
| "eval_f1": 0.8338557993730408, | |
| "eval_loss": 0.07030046731233597, | |
| "eval_precision": 0.9568345323741008, | |
| "eval_recall": 0.7388888888888889, | |
| "eval_runtime": 20.4927, | |
| "eval_samples_per_second": 8.784, | |
| "eval_steps_per_second": 2.196, | |
| "step": 525 | |
| } | |
| ], | |
| "logging_steps": 20, | |
| "max_steps": 630, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 6, | |
| "save_steps": 500, | |
| "stateful_callbacks": { | |
| "TrainerControl": { | |
| "args": { | |
| "should_epoch_stop": false, | |
| "should_evaluate": false, | |
| "should_log": false, | |
| "should_save": true, | |
| "should_training_stop": false | |
| }, | |
| "attributes": {} | |
| } | |
| }, | |
| "total_flos": 5724731813068800.0, | |
| "train_batch_size": 4, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |