Question Answering
Transformers
Safetensors
grt
extractive-qa
squad
rotational-transformer
givens-rotations
clifford-algebra
matterwave
Instructions to use MatterWaveAI/grt-30m-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MatterWaveAI/grt-30m-qa with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="MatterWaveAI/grt-30m-qa")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForQuestionAnswering model = AutoModelForQuestionAnswering.from_pretrained("MatterWaveAI/grt-30m-qa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Release MatterWaveAI/grt-30m-qa (100% rotational head + 8-way geometric optimizer ablation)
92454d2 verified Download eval_results.json from MatterWaveAI/grt-30m-qa: direct link, hf CLI and curl.
- Browser
- Download file 3.97 kB
-
https://huggingface.co/MatterWaveAI/grt-30m-qa/resolve/main/eval_results.json
- Command line
-
hf download hf://MatterWaveAI/grt-30m-qa/eval_results.json
-
curl -L -o eval_results.json https://huggingface.co/MatterWaveAI/grt-30m-qa/resolve/main/eval_results.json
3.97 kB
| { | |
| "model_id": "MatterWaveAI/grt-30m-qa", | |
| "architecture": "GRTForQuestionAnswering", | |
| "base_model": "MatterWaveAI/grt-30m", | |
| "parameters": 29306020, | |
| "trainable_parameters": 812430, | |
| "nn_linear_layers": 0, | |
| "nn_conv1d_layers": 0, | |
| "num_labels": 2, | |
| "best_optimizer": "polar_natural_adam", | |
| "benchmarks": { | |
| "squad_extractive_qa_val": { | |
| "val_span_loss": 0.6512, | |
| "exact_match": 75.0, | |
| "span_token_f1": 83.57, | |
| "start_acc": 83.75, | |
| "end_acc": 76.25 | |
| }, | |
| "step0_untrained_head": { | |
| "val_span_loss": 8.9793, | |
| "exact_match": 0.0, | |
| "span_token_f1": 0.45, | |
| "start_acc": 3.75, | |
| "end_acc": 0.0 | |
| } | |
| }, | |
| "optimizer_ablation_8way": { | |
| "pair_adam": { | |
| "optimizer_type": "pair_adam", | |
| "variant": "PairAdam (Factored Toroidal Baseline)", | |
| "final_train_loss": 0.1383, | |
| "last_batch_train_loss": 0.5309, | |
| "val_span_loss": 0.6532, | |
| "exact_match": 75.0, | |
| "span_token_f1": 83.57, | |
| "start_acc": 83.75, | |
| "end_acc": 76.25, | |
| "wall_time_s": 207.23 | |
| }, | |
| "hessian_pair_adam": { | |
| "optimizer_type": "hessian_pair_adam", | |
| "variant": "HessianPairAdam (Sophia-Torus Cauchy-Riemann Curvature)", | |
| "final_train_loss": 0.1387, | |
| "last_batch_train_loss": 0.5307, | |
| "val_span_loss": 0.6506, | |
| "exact_match": 73.75, | |
| "span_token_f1": 83.39, | |
| "start_acc": 83.75, | |
| "end_acc": 75.0, | |
| "wall_time_s": 232.96 | |
| }, | |
| "polar_natural_adam": { | |
| "optimizer_type": "polar_natural_adam", | |
| "variant": "PolarNaturalAdam (Riemannian Polar Metric + Cauchy-Riemann Hessian)", | |
| "final_train_loss": 0.1385, | |
| "last_batch_train_loss": 0.5308, | |
| "val_span_loss": 0.6512, | |
| "exact_match": 75.0, | |
| "span_token_f1": 83.57, | |
| "start_acc": 83.75, | |
| "end_acc": 76.25, | |
| "wall_time_s": 219.08 | |
| }, | |
| "cyclide_adam": { | |
| "optimizer_type": "cyclide_adam", | |
| "variant": "CyclideAdam (Dupin Cyclide Conic Metric + Deviatoric Twist)", | |
| "final_train_loss": 0.1382, | |
| "last_batch_train_loss": 0.5305, | |
| "val_span_loss": 0.652, | |
| "exact_match": 75.0, | |
| "span_token_f1": 83.57, | |
| "start_acc": 83.75, | |
| "end_acc": 76.25, | |
| "wall_time_s": 225.19 | |
| }, | |
| "symplectic_adam": { | |
| "optimizer_type": "symplectic_adam", | |
| "variant": "SymplecticAdam (Gromov-Liouville Non-Squeezing Floor + Casimir Cavity)", | |
| "final_train_loss": 0.1391, | |
| "last_batch_train_loss": 0.5317, | |
| "val_span_loss": 0.6537, | |
| "exact_match": 75.0, | |
| "span_token_f1": 83.57, | |
| "start_acc": 83.75, | |
| "end_acc": 76.25, | |
| "wall_time_s": 261.38 | |
| }, | |
| "gyric_adam": { | |
| "optimizer_type": "gyric_adam", | |
| "variant": "GyricAdam (Poinsot-Lande Gyroscopic Projection + Thomas Precession)", | |
| "final_train_loss": 0.1393, | |
| "last_batch_train_loss": 0.532, | |
| "val_span_loss": 0.6541, | |
| "exact_match": 75.0, | |
| "span_token_f1": 83.57, | |
| "start_acc": 83.75, | |
| "end_acc": 76.25, | |
| "wall_time_s": 221.44 | |
| }, | |
| "huygens_adam": { | |
| "optimizer_type": "huygens_adam", | |
| "variant": "HuygensAdam (Circular Order Parameter R_p Splay Torque)", | |
| "final_train_loss": 0.1378, | |
| "last_batch_train_loss": 0.532, | |
| "val_span_loss": 0.6557, | |
| "exact_match": 75.0, | |
| "span_token_f1": 83.57, | |
| "start_acc": 83.75, | |
| "end_acc": 76.25, | |
| "wall_time_s": 152.14 | |
| }, | |
| "huygens_symplectic_adam": { | |
| "optimizer_type": "huygens_symplectic_adam", | |
| "variant": "HuygensSymplecticAdam (Two-Stage Huygens -> Symplectic Curriculum)", | |
| "final_train_loss": 0.1391, | |
| "last_batch_train_loss": 0.5317, | |
| "val_span_loss": 0.6537, | |
| "exact_match": 75.0, | |
| "span_token_f1": 83.57, | |
| "start_acc": 83.75, | |
| "end_acc": 76.25, | |
| "wall_time_s": 146.7 | |
| } | |
| } | |
| } | |