Update README.md
Browse files
README.md
CHANGED
@@ -1,3 +1,67 @@
|
|
1 |
---
|
2 |
license: apache-2.0
|
|
|
|
|
|
|
|
|
|
|
3 |
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
---
|
2 |
license: apache-2.0
|
3 |
+
datasets:
|
4 |
+
- bookcorpus
|
5 |
+
- wikipedia
|
6 |
+
language:
|
7 |
+
- en
|
8 |
---
|
9 |
+
|
10 |
+
# BERT Small (uncased)
|
11 |
+
|
12 |
+
Mini BERT models from https://arxiv.org/abs/1908.08962 that the HF team didn't convert. The original [conversion script](https://github.com/huggingface/transformers/blob/main/src/transformers/models/bert/convert_bert_original_tf_checkpoint_to_pytorch.py) is used.
|
13 |
+
|
14 |
+
See the original Google repo: [google-research/bert](https://github.com/google-research/bert)
|
15 |
+
|
16 |
+
Note: it's not clear if these checkpoints have undergone knowledge distillation.
|
17 |
+
|
18 |
+
## Model variants
|
19 |
+
|
20 |
+
| |H=128|H=256|H=512|H=768|
|
21 |
+
|---|:---:|:---:|:---:|:---:|
|
22 |
+
| **L=2** |[2/128 (BERT-Tiny)][2_128]|[2/256][2_256]|[2/512][2_512]|[2/768][2_768]|
|
23 |
+
| **L=4** |[4/128][4_128]|[4/256 (BERT-Mini)][4_256]|[**4/512 (BERT-Small)**][4_512]|[4/768][4_768]|
|
24 |
+
| **L=6** |[6/128][6_128]|[6/256][6_256]|[6/512][6_512]|[6/768][6_768]|
|
25 |
+
| **L=8** |[8/128][8_128]|[8/256][8_256]|[8/512 (BERT-Medium)][8_512]|[8/768][8_768]|
|
26 |
+
| **L=10** |[10/128][10_128]|[10/256][10_256]|[10/512][10_512]|[10/768][10_768]|
|
27 |
+
| **L=12** |[12/128][12_128]|[12/256][12_256]|[12/512][12_512]|[12/768 (BERT-Base, original)][12_768]|
|
28 |
+
|
29 |
+
[2_128]: https://huggingface.co/gaunernst/bert-tiny-uncased
|
30 |
+
[2_256]: https://huggingface.co/gaunernst/bert-L2-H256-uncased
|
31 |
+
[2_512]: https://huggingface.co/gaunernst/bert-L2-H512-uncased
|
32 |
+
[2_768]: https://huggingface.co/gaunernst/bert-L2-H768-uncased
|
33 |
+
[4_128]: https://huggingface.co/gaunernst/bert-L4-H128-uncased
|
34 |
+
[4_256]: https://huggingface.co/gaunernst/bert-mini-uncased
|
35 |
+
[4_512]: https://huggingface.co/gaunernst/bert-small-uncased
|
36 |
+
[4_768]: https://huggingface.co/gaunernst/bert-L4-H768-uncased
|
37 |
+
[6_128]: https://huggingface.co/gaunernst/bert-L6-H128-uncased
|
38 |
+
[6_256]: https://huggingface.co/gaunernst/bert-L6-H256-uncased
|
39 |
+
[6_512]: https://huggingface.co/gaunernst/bert-L6-H512-uncased
|
40 |
+
[6_768]: https://huggingface.co/gaunernst/bert-L6-H768-uncased
|
41 |
+
[8_128]: https://huggingface.co/gaunernst/bert-L8-H128-uncased
|
42 |
+
[8_256]: https://huggingface.co/gaunernst/bert-L8-H256-uncased
|
43 |
+
[8_512]: https://huggingface.co/gaunernst/bert-medium-uncased
|
44 |
+
[8_768]: https://huggingface.co/gaunernst/bert-L8-H768-uncased
|
45 |
+
[10_128]: https://huggingface.co/gaunernst/bert-L10-H128-uncased
|
46 |
+
[10_256]: https://huggingface.co/gaunernst/bert-L10-H256-uncased
|
47 |
+
[10_512]: https://huggingface.co/gaunernst/bert-L10-H512-uncased
|
48 |
+
[10_768]: https://huggingface.co/gaunernst/bert-L10-H768-uncased
|
49 |
+
[12_128]: https://huggingface.co/gaunernst/bert-L12-H128-uncased
|
50 |
+
[12_256]: https://huggingface.co/gaunernst/bert-L12-H256-uncased
|
51 |
+
[12_512]: https://huggingface.co/gaunernst/bert-L12-H512-uncased
|
52 |
+
[12_768]: https://huggingface.co/bert-base-uncased
|
53 |
+
|
54 |
+
## Usage
|
55 |
+
|
56 |
+
See other BERT model cards e.g. https://huggingface.co/bert-base-uncased
|
57 |
+
|
58 |
+
## Citation
|
59 |
+
|
60 |
+
```bibtex
|
61 |
+
@article{turc2019,
|
62 |
+
title={Well-Read Students Learn Better: On the Importance of Pre-training Compact Models},
|
63 |
+
author={Turc, Iulia and Chang, Ming-Wei and Lee, Kenton and Toutanova, Kristina},
|
64 |
+
journal={arXiv preprint arXiv:1908.08962v2 },
|
65 |
+
year={2019}
|
66 |
+
}
|
67 |
+
```
|