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description: All the settings needed for creating an experiment are explored in this page.
import GeneralSettingsDataset from '../../tooltips/experiments/_dataset.mdx'; import GeneralSettingsProblemType from '../../tooltips/experiments/_problem-type.mdx'; import GSImportConfigFromYaml from '../../tooltips/experiments/_import-config-from-yaml.mdx'; import GSExperimentName from '../../tooltips/experiments/_experiment-name.mdx'; import GSLLMBackbone from '../../tooltips/experiments/_llm-backbone.mdx'; import DSTrainDataframe from '../../tooltips/experiments/_train-dataframe.mdx'; import DSvalidationStrategy from '../../tooltips/experiments/_validation-strategy.mdx'; import DSvalidationSize from '../../tooltips/experiments/_validation-size.mdx'; import DSdataSample from '../../tooltips/experiments/_data-sample.mdx'; import DSpromptColumn from '../../tooltips/experiments/_prompt-column.mdx'; import DSPromptColumnSeparator from '../../tooltips/experiments/_prompt-column-separator.mdx'; import DSsystemColumn from '../../tooltips/experiments/_system-column.mdx'; import DSanswerColumn from '../../tooltips/experiments/_answer-column.mdx'; import DSparentIdColumn from '../../tooltips/experiments/_parent-id-column.mdx'; import DStextPromptStart from '../../tooltips/experiments/_text-prompt-start.mdx'; import DStextAnswerSeparator from '../../tooltips/experiments/_text-answer-separator.mdx'; import DSaddEosTokentoprompt from '../../tooltips/experiments/_add-eos-token-to-prompt.mdx'; import DSaddEosTokentoanswer from '../../tooltips/experiments/_add-eos-token-to-answer.mdx'; import DSmaskPromptlabels from '../../tooltips/experiments/_mask-prompt-labels.mdx'; import TSmaxLength from '../../tooltips/experiments/_max-length.mdx'; import TSaddpromptanswertokens from '../../tooltips/experiments/_add-prompt-answer-tokens.mdx'; import TSpaddingQuantile from '../../tooltips/experiments/_padding-quantile.mdx'; import ASBackboneDtype from '../../tooltips/experiments/_backbone-dtype.mdx'; import ASGradientcheckpointing from '../../tooltips/experiments/_gradient-checkpointing.mdx'; import ASintermediateDropout from '../../tooltips/experiments/_intermediate-dropout.mdx'; import ASpretrainedWeights from '../../tooltips/experiments/_pretrained-weights.mdx'; import TSoptimizer from '../../tooltips/experiments/_optimizer.mdx'; import TSlossfunction from '../../tooltips/experiments/_loss-function.mdx'; import TSlearningRate from '../../tooltips/experiments/_learning-rate.mdx'; import TSdifferentialLearningRateLayers from '../../tooltips/experiments/_differential-learning-rate-layers.mdx'; import TSfreezeLayers from '../../tooltips/experiments/_freeze-layers.mdx'; import TSattentionImplementation from '../../tooltips/experiments/_attention-implementation.mdx'; import TSbatchSize from '../../tooltips/experiments/_batch-size.mdx'; import TSepochs from '../../tooltips/experiments/_epochs.mdx'; import TSschedule from '../../tooltips/experiments/_schedule.mdx'; import TSminLearningRateRatio from '../../tooltips/experiments/_min-learning-rate-ratio.mdx'; import TSwarmupEpochs from '../../tooltips/experiments/_warmup-epochs.mdx'; import TSweightDecay from '../../tooltips/experiments/_weight-decay.mdx'; import TSGradientclip from '../../tooltips/experiments/_gradient-clip.mdx'; import TSgradAccumulation from '../../tooltips/experiments/_grad-accumulation.mdx'; import TSlora from '../../tooltips/experiments/_lora.mdx'; import TSuseDora from '../../tooltips/experiments/_use-dora.mdx'; import TSloraR from '../../tooltips/experiments/_lora-r.mdx'; import TSloraAlpha from '../../tooltips/experiments/_lora-alpha.mdx'; import TSloraDropout from '../../tooltips/experiments/_lora-dropout.mdx'; import TSuseRSlora from '../../tooltips/experiments/_use-rslora.mdx'; import TSloraTargetModules from '../../tooltips/experiments/_lora-target-modules.mdx'; import TSloraUnfreezeLayers from '../../tooltips/experiments/_lora-unfreeze-layers.mdx'; import TSsavecheckpoint from '../../tooltips/experiments/_save-checkpoint.mdx'; import TSevaluationepochs from '../../tooltips/experiments/_evaluation-epochs.mdx'; import TSevaluationbeforetraining from '../../tooltips/experiments/_evaluate-before-training.mdx'; import TStrainvalidationdata from '../../tooltips/experiments/_train-validation-data.mdx'; import AStokenmaskprobability from '../../tooltips/experiments/_token-mask-probability.mdx'; import ASskipParentprobability from '../../tooltips/experiments/_skip-parent-probability.mdx'; import ASrandomparentprobability from '../../tooltips/experiments/_random-parent-probability.mdx'; import ASneftunenoisealpha from '../../tooltips/experiments/_neftune_noise_alpha.mdx'; import PSmetric from '../../tooltips/experiments/_metric.mdx'; import PSmetricgptmodel from '../../tooltips/experiments/_metric-gpt-model.mdx'; import PSmetricgpttemplate from '../../tooltips/experiments/_metric-gpt-template.mdx'; import PSminlengthinference from '../../tooltips/experiments/_min-length-inference.mdx'; import PSmaxlengthinference from '../../tooltips/experiments/_max-length-inference.mdx'; import PSbatchsizeinference from '../../tooltips/experiments/_batch-size-inference.mdx'; import PSdosample from '../../tooltips/experiments/_do-sample.mdx'; import PSnumbeams from '../../tooltips/experiments/_num-beams.mdx'; import PStemperature from '../../tooltips/experiments/_temperature.mdx'; import PSrepetitionpenalty from '../../tooltips/experiments/_repetition-penalty.mdx'; import PSstoptokens from '../../tooltips/experiments/_stop-tokens.mdx'; import PStopk from '../../tooltips/experiments/_top-k.mdx'; import PStopp from '../../tooltips/experiments/_top-p.mdx'; import ESgpus from '../../tooltips/experiments/_gpus.mdx'; import ESmixedprecision from '../../tooltips/experiments/_mixed-precision.mdx'; import EScompilemodel from '../../tooltips/experiments/_compile-model.mdx'; import ESfindunusedparameters from '../../tooltips/experiments/_find-unused-parameters.mdx'; import EStrustremotecode from '../../tooltips/experiments/_trust-remote-code.mdx'; import EShuggingfacebranch from '../../tooltips/experiments/_huggingface-branch.mdx'; import ESnumofworkers from '../../tooltips/experiments/_number-of-workers.mdx'; import ESseed from '../../tooltips/experiments/_seed.mdx'; import LSlogstepsize from '../../tooltips/experiments/_log-step-size.mdx'; import LSlogallranks from '../../tooltips/experiments/_log-all-ranks.mdx'; import LSlogger from '../../tooltips/experiments/_logger.mdx'; import LSneptuneproject from '../../tooltips/experiments/_neptune-project.mdx'; import LSwandbproject from '../../tooltips/experiments/_wandb-project.mdx'; import LSwandbentity from '../../tooltips/experiments/_wandb-entity.mdx'; import NumClasses from '../../tooltips/experiments/_num-classes.mdx';
Experiment settings
The settings for creating an experiment are grouped into the following sections:
- General settings
- Dataset settings
- Tokenizer settings
- Architecture settings
- Training settings
- Augmentation settings
- Prediction settings
- Environment settings
- Logging settings
The settings under each category are listed and described below.
General settings
Dataset
Problem type
Import config from YAML
Experiment name
LLM backbone
Dataset settings
Train dataframe
Validation strategy
Validation size
Data sample
System column
Prompt column
Prompt column separator
Answer column
Parent ID column
ID column
Text prompt start
Text answer separator
Add EOS token to prompt
Add EOS token to answer
Mask prompt labels
Num classes
The Num classes field should be set to the total number of classes in the answer column of the dataset.
Tokenizer settings
Max length
Add prompt answer tokens
Padding quantile
Architecture settings
Backbone Dtype
Gradient Checkpointing
Intermediate dropout
Pretrained weights
Training settings
Loss function
For multiclass classification problems, set the loss function to Cross-entropy.
Optimizer
Learning rate
Differential learning rate layers
By default, H2O LLM Studio applies Differential learning rate Layers, with the learning rate for the classification_head being 10 times smaller than the learning rate for the rest of the model.