WiggleGPT / task_adaptations /sst2 /metadata.json
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Add task-specific WiggleGPT checkpoints and results
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{
"format": "wigglegpt_task_inference_v1",
"task": "sst2",
"model_args": {
"block_size": 1024,
"vocab_size": 50304,
"n_layer": 12,
"n_head": 12,
"n_embd": 768,
"dropout": 0.0,
"bias": false,
"use_bio_mlp": true,
"use_rmsnorm": true,
"use_rope": true,
"gradient_checkpointing": false
},
"markers": {
"start": 50257,
"delimiter": 50258,
"classify": 50259,
"pad": 50256
},
"config": {
"starting_checkpoint": "ckpt_pretrain.pt (original 600,000-step pretrained model)",
"epochs": 3,
"effective_batch_size": 32,
"learning_rate": 6.25e-05,
"warmup_fraction": 0.002,
"schedule": "linear warmup then linear decay, matching GPT-1 task adaptation",
"lm_coefficient": 0.5,
"classifier_dropout": 0.1,
"weight_decay": 0.01,
"betas": [
0.9,
0.999
],
"epsilon": 1e-08,
"grad_clip": 1.0,
"max_length": 512,
"seed": 42,
"cpu_threads": 2,
"desktop_reserve_gib": 2.5,
"max_process_gib": 9.0,
"checkpoint_interval": 500,
"log_interval": 25,
"max_consecutive_nonfinite": 8,
"tasks": {
"sst2": {
"microbatch_size": 16,
"gradient_checkpointing": false,
"eval_interval": 1000
},
"race_middle": {
"microbatch_size": 2,
"gradient_checkpointing": true,
"eval_interval": 400
}
}
},
"task_config": {
"max_length": 512,
"classifier_dropout": 0.1,
"label_names": [
"negative",
"positive"
],
"head": "768-to-2 linear",
"task_head_parameters": 1538,
"input_layout": "[start] review [classify]",
"truncation": "review tokens truncated only if required to fit 512 total tokens",
"tokenizer": "GPT-2 r50k_base",
"tokenizer_merges_sha256": "306cd27f03c1a714eca7108e03d66b7dc042abe8c258b44c199a7ed9838dd930",
"right_padding": true,
"minimum_padded_width": 16,
"classification_position": "last non-padding token (classify marker)",
"state_key_prefixes": [
"base.",
"classifier."
],
"requires_custom_wrapper": true
},
"training": {
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"max_steps": 6315,
"steps": 6315,
"batch_size": 32,
"microbatch_size": 16,
"gradient_accumulation": 2,
"learning_rate": 6.25e-05,
"max_length": 512,
"lm_coefficient": 0.5,
"stopping_cause": "epochs_complete",
"classifier_dropout": 0.1,
"native_backbone_dropout": 0.0,
"nonfinite_updates": 0,
"best_step": 6315,
"peak_allocated_gib": 3.846,
"trainable_parameters": 123699458,
"head": "768-to-2 linear",
"checkpoint_selection": "highest validation accuracy, lower validation classification loss breaks ties",
"details": "Full native backbone trained. Zero decay on oscillator and 1-D parameters. Linear GPT-1 warmup/decay, AdamW, gradient clip1.0. Original backbone dropout retained; classifier dropout0.1. Three unused padding-vocabulary slots initialized for task markers.",
"data_truncation": {
"train": {
"examples_with_truncation": 0,
"candidate_sequences_with_truncation": 0,
"total_tokens_removed": 0,
"max_tokens_removed_per_example": 0
},
"validation": {
"examples_with_truncation": 0,
"candidate_sequences_with_truncation": 0,
"total_tokens_removed": 0,
"max_tokens_removed_per_example": 0
}
},
"segments": 2
},
"metrics": {
"heldout_split": "validation",
"before": {
"label": "Before task training (same classifier)",
"correct": 437,
"total": 872,
"accuracy": 0.5011467889908257,
"loss": 4.14792537689209,
"gold_label_counts": [
428,
444
],
"majority_accuracy": 0.5091743119266054
},
"after": {
"correct": 786,
"total": 872,
"accuracy": 0.9013761467889908,
"loss": 0.29649588465690613,
"gold_label_counts": [
428,
444
],
"majority_accuracy": 0.5091743119266054
},
"confusion_matrix": {
"before": [
[
398,
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],
[
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]
],
"after": [
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],
[
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]
},
"train_examples": 67349,
"validation_examples": 872,
"test_examples": 1821
},
"provenance": {
"source_training_checkpoint": "best.pt",
"source_training_checkpoint_sha256": "2e2630c24231098e9381b09b2e6f3d27a273696743bfe65bffe4d5f2ecd4d80e",
"source_hashes": {
"model": "a28201b8194941a75d3ca2e0812e6d2d0eef1b2656cc0c9f8fd0ca65bf96b28b",
"trainer": "550f68528e3dbe630cb7f0ad29860d8bafb77767832819dab86ea598a29ad520"
},
"original_pretrained_checkpoint_sha256": "88afaab6c93ef3e33940b4e25cbce2f44038c428109600afe8285586a3a767b9",
"original_backbone_unchanged_during_export": true,
"task_weights": "independent full-model task adaptation of original pretrained backbone",
"export": "CPU state-dict serialization only; optimizer, order and RNG removed; no model construction or forward pass",
"torch_version": "2.11.0.dev20260215+cu128"
},
"file": "model.pt",
"bytes": 494839923,
"sha256": "0a0c73b9ec95da128c07abe6949abd2db8492c829f52bd7bb350f67aef684c66",
"validation": "All model tensors exactly equal to the completed best checkpoint; source SHA-256 matches comparison record."
}