| { |
| "browser_note": "Same input and output names as the full M1 SciBERT ONNX export; can query semantic_m1 paper vector files.", |
| "built_at": 1777171028, |
| "dimension": 768, |
| "interactive_level": "exports/huggingface/paper_universe_interactive_v1/interactive/papers_all.json", |
| "model_kind": "m1_lite_distilled_embedding", |
| "normalization": "l2", |
| "onnx": "onnx/model.onnx", |
| "pooling": "mean_pool_attention_mask_project_l2_normalized", |
| "quantized_onnx": "onnx/model.int8.onnx", |
| "scale": 127.0, |
| "sequence_length": 128, |
| "source_dir": "/arxiv/huggingface/paper_text_1m_dedup_v1", |
| "student_id": "google/bert_uncased_L-4_H-256_A-4", |
| "target_embeddings": "exports/huggingface/paper_universe_interactive_v1/semantic_m1/papers_all.emb.i8", |
| "teacher_base_id": "allenai/scibert_scivocab_uncased", |
| "teacher_id": "PeytonT/1m-paper-embedding-model", |
| "tokenizer": "tokenizer", |
| "train_stats": { |
| "eval_cosine": 0.7350965235382318, |
| "eval_mse": 0.0006898527972225565, |
| "final_cosine": 0.739337682723999, |
| "final_loss": 0.2609059512615204, |
| "global_steps": 7813, |
| "missing_texts": 0, |
| "rows": 1000000, |
| "train_seconds": 473.90148282051086 |
| } |
| } |
|
|
