TensorBERT-FT artifacts
Training checkpoints and evaluation outputs produced by the 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.