disable pre_ffn and head_qk
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@ -116,9 +116,9 @@ const loraFinetuneParametersOptions: Array<[key: keyof LoraFinetuneParameters, t
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['loraR', 'number', 'LoRA R'],
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['loraR', 'number', 'LoRA R'],
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['loraAlpha', 'number', 'LoRA Alpha'],
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['loraAlpha', 'number', 'LoRA Alpha'],
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['loraDropout', 'number', 'LoRA Dropout'],
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['loraDropout', 'number', 'LoRA Dropout'],
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['beta1', 'any', ''],
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['beta1', 'any', '']
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['preFfn', 'boolean', 'Pre-FFN'],
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// ['preFfn', 'boolean', 'Pre-FFN'],
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['headQk', 'boolean', 'Head QK']
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// ['headQk', 'boolean', 'Head QK']
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];
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];
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const showError = (e: any) => {
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const showError = (e: any) => {
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@ -304,7 +304,7 @@ const LoraFinetune: FC = observer(() => {
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`--ctx_len ${ctxLen} --epoch_steps ${loraParams.epochSteps} --epoch_count ${loraParams.epochCount} ` +
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`--ctx_len ${ctxLen} --epoch_steps ${loraParams.epochSteps} --epoch_count ${loraParams.epochCount} ` +
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`--epoch_begin ${loraParams.epochBegin} --epoch_save ${loraParams.epochSave} ` +
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`--epoch_begin ${loraParams.epochBegin} --epoch_save ${loraParams.epochSave} ` +
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`--micro_bsz ${loraParams.microBsz} --accumulate_grad_batches ${loraParams.accumGradBatches} ` +
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`--micro_bsz ${loraParams.microBsz} --accumulate_grad_batches ${loraParams.accumGradBatches} ` +
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`--pre_ffn ${loraParams.preFfn ? '1' : '0'} --head_qk ${loraParams.headQk ? '1' : '0'} --lr_init ${loraParams.lrInit} --lr_final ${loraParams.lrFinal} ` +
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`--pre_ffn ${loraParams.preFfn ? '0' : '0'} --head_qk ${loraParams.headQk ? '0' : '0'} --lr_init ${loraParams.lrInit} --lr_final ${loraParams.lrFinal} ` +
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`--warmup_steps ${loraParams.warmupSteps} ` +
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`--warmup_steps ${loraParams.warmupSteps} ` +
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`--beta1 ${loraParams.beta1} --beta2 ${loraParams.beta2} --adam_eps ${loraParams.adamEps} ` +
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`--beta1 ${loraParams.beta1} --beta2 ${loraParams.beta2} --adam_eps ${loraParams.adamEps} ` +
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`--devices ${loraParams.devices} --precision ${loraParams.precision} ` +
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`--devices ${loraParams.devices} --precision ${loraParams.precision} ` +
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