Add archive model card

README.md

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+---
+license: other
+library_name: transformers
+tags:
+  - bert
+  - tensorized
+  - pytorch
+  - rte
+  - research-artifact
+---
+
+# colaBertFt checkpoint archive
+
+This repository is a preservation archive for checkpoints produced by the
+[`colaBertFt`](https://github.com/iAmALai/colaBertFt) research code. The models
+use a BERT-large-shaped architecture with tensorized attention and feed-forward
+layers. One pair uses low-rank activations throughout; the other restricts the
+low-rank activation behavior according to `only_lr_act` in its config.
+
+This is an archival release, not a polished inference package. Loading the
+exports may require the custom modeling code in the source repository.
+
+## Contents
+
+| Remote path | Description |
+|---|---|
+| `bak/chkpt_not_onlylr.pt` | Epoch-2 PyTorch training snapshot with model, optimizer, gradient-scaler, and epoch state. |
+| `bak/chkpt_onlylr.pt` | Epoch-2 `only_lr_act` training snapshot with model, optimizer, gradient-scaler, and epoch state. |
+| `checkpoints/cola_bert_llama_mlp_large_0.7-004/` | FP16 model state dict and architecture config corresponding exactly to the model tensors in `bak/chkpt_not_onlylr.pt`. |
+| `checkpoints/cola_bert_llama_mlp_large_0.7_only_lr-001/` | FP16 model state dict and architecture config corresponding exactly to the model tensors in `bak/chkpt_onlylr.pt`. |
+| `model_checkpoints/rte_cola_bert_llama_mlp_large_0.7_only_lr-001/` | PyTorch Lightning RTE checkpoint from epoch 1/global step 68. Its filename records validation accuracy 0.7329; this archive did not independently reproduce that evaluation. |
+| `model_checkpoints/colaBert_rte_mlpId_0.7329_2e2e91ae/` | Converted FP16 safetensors RTE export, config, and the original generated model card. |
+
+Exact SHA-256 checksums are stored in `ARTIFACT_CHECKSUMS.sha256` here and in
+the source repository.
+
+## Provenance and training
+
+- Base model named by the training configuration: `bert-large-uncased`.
+- Downstream task: GLUE RTE.
+- RTE Lightning checkpoint metadata: 2 labels, 2,490 training samples,
+  learning rate 2e-5, Adam epsilon 1e-8, warmup proportion 0.1, weight decay
+  0.01, and 117 planned training steps.
+- Archive source files were created in August and September 2025 and archived
+  in July 2026.
+
+The two 2.4 GB training snapshots contain optimizer state and are retained for
+exact training-resume preservation. Their 615 model tensors match their
+corresponding smaller `model.pt` exports exactly.
+
+## Loading and safety
+
+The `.pt` and `.ckpt` files use Python/PyTorch serialization. Only load them
+when you trust this archive, and prefer a current PyTorch release with
+`weights_only=True` where compatible. The `.safetensors` export avoids pickle
+deserialization but still requires the matching custom architecture.
+
+These artifacts are research outputs and have not been audited for production
+use, bias, robustness, or generalization beyond the recorded RTE experiment.
+
+## Licensing
+
+The upstream `bert-large-uncased` model is distributed under Apache-2.0. The
+source project does not currently declare a license of its own, so this archive
+does not make an additional licensing grant for the custom code or derived
+artifacts. Users are responsible for checking the applicable upstream terms.