Added more training parameters; Removed chat emulation of text datasets; Fixes;
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@@ -9,10 +9,6 @@ purgeTargetDirectories=false
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train=true
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# save lora adapter to disk after training. Also required for validation and merging
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storeAdapter=true
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# convert text dataset to chat prompts
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trTextDsToChat=true
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# if plain texts have been converted to chat prompts, also keep plain texts in dataset (combined)
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trTextDsKeepPlainText=true
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# path to base model (hf safetensors repo)
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locBaseModel=../../lm/models/safetensors/Qwen2.5-1.5B-Instruct/
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# path to datasets
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@@ -24,9 +20,14 @@ locAdapter=./testProject/adapter/
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# training epochs (how many times each dataset entry is trained)
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# vInplace true: Validation will run after each batch of training epochs until vExpected has been reached, otherwise the next training batch starts
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# vInplace false: Training is executed once for trEpochs epochs
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# Optimizer schedule_free_*: Leave trEpochs blank
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trEpochs=10
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# optional int, maximum length of training sequence
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trMaxSeqLength=
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# optional scheduler type: linear, constant, cosine, polynomial, inverse_sqrt
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trSchedulerType=
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# optional optimizer; grokadamw, schedule_free_adamw, schedule_free_sgd
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trOptim=
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# optional int, training batch size (reduces memory consumption)
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trPerDeviceTrainBatchSize=
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# optional bool, determine training batch size (reduces memory consumption)
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