---
tags:
- tensorbert
- bert
- glue
- pytorch
---

# TensorBERT-FT artifacts

Training checkpoints and evaluation outputs produced by the
[TensorBERT-FT](https://github.com/alvin-zyl/TensorBERT-FT) codebase.

## Local artifact inventory

Inventory taken on 2026-07-30. Sizes are binary units (GiB/MiB).

| Local path | Size | Contents |
|---|---:|---|
| `tensor-/results/glue/` | 32.3 GiB | 35 fine-tuned GLUE checkpoints plus configs, metrics, and logs |
| `weights/` | 13.2 GiB | 6 pretrained/intermediate `.pt` checkpoints |
| `glue_data/` | 2.9 GiB | Local GLUE data and preprocessing caches; intentionally not uploaded |
| Remaining source tree | < 3 MiB | Code, notebooks, and metadata |
| **Total local tree** | **48.1 GiB** | 396 regular files |

By file type, the large artifacts are approximately 32.3 GiB in 35 `.bin`
files, 13.2 GiB in 6 `.pt` files, and 1.4 GiB in 43 extensionless files.
There are 46 files larger than 100 MiB, totaling about 48.0 GiB.

The local directory's measured size was 49 GiB as rounded by `du -h`, both
for allocated and apparent size. It was not 76 GB at inventory time.

## Checkpoint groups

The 35 fine-tuned result checkpoints are each about 944 MiB:

| Group | Checkpoints | Approximate size |
|---|---:|---:|
| CoLA | 2 | 1.8 GiB |
| MRPC | 10 | 9.2 GiB |
| RTE `0_7-004` sweep | 10 | 9.2 GiB |
| RTE `0_7_only_lr-001` sweep | 10 | 9.2 GiB |
| Other RTE | 2 | 1.8 GiB |
| WNLI | 1 | 0.9 GiB |

The six files under `weights/` are:

| Path | Approximate size |
|---|---:|
| `weights/bert_large/model.pt` | 3.2 GiB |
| `weights/bert_large/ckpt_8038.pt` | 3.2 GiB |
| `weights/cola_bert_llama_mlp_large_0.7-004/model.pt` | 2.4 GiB |
| `weights/cola_bert_llama_mlp_large_0.7_only_lr-001/model.pt` | 2.4 GiB |
| `weights/tensor_bert/model.pt` | 1.2 GiB |
| `weights/tensor_bert/ckpt_8038.pt` | 1.2 GiB |

## Curated evaluation checkpoints

The curated upload profile selects the best observed validation result in
each available task/group:

| Task | Local run | Validation metric |
|---|---|---:|
| CoLA | `COLA-0_lr_only` | MCC 0.4519 |
| MRPC | `MRPC-3_32_8` | accuracy/F1 mean 0.8774 |
| RTE | `RTE-0_7_only_lr-001_6_32_8` | accuracy 0.6968 |
| WNLI | `WNLI` | accuracy 0.5634 |

These values are copied from each run's `results.txt`; they are not an
independent reproduction.

## Duplicate note

SHA-256 inventory found that `results/glue/RTE/pytorch_model.bin` and
`results/glue/RTE-0_7-004_3_32_8/pytorch_model.bin` are byte-identical. The
full-results upload omits the former duplicate directory. Other large files
had distinct SHA-256 hashes.

## Scope and reuse

The GLUE dataset files and preprocessing caches are not included. Obtain the
original datasets from their authoritative distributors and follow their
respective licenses. The license/provenance of the checkpoint weights should
be confirmed by the uploader before representing these artifacts as freely
redistributable.