CollectionStudio julien-c HF Staff commited on
Commit
1afda92
·
0 Parent(s):

Duplicate from microsoft/deberta-base

Browse files

Co-authored-by: Julien Chaumond <julien-c@users.noreply.huggingface.co>

Files changed (10) hide show
  1. .gitattributes +8 -0
  2. README.md +40 -0
  3. bpe_encoder.bin +3 -0
  4. config.json +19 -0
  5. merges.txt +0 -0
  6. pytorch_model.bin +3 -0
  7. rust_model.ot +3 -0
  8. tf_model.h5 +3 -0
  9. tokenizer_config.json +4 -0
  10. vocab.json +0 -0
.gitattributes ADDED
@@ -0,0 +1,8 @@
 
 
 
 
 
 
 
 
 
1
+ *.bin.* filter=lfs diff=lfs merge=lfs -text
2
+ *.lfs.* filter=lfs diff=lfs merge=lfs -text
3
+ *.bin filter=lfs diff=lfs merge=lfs -text
4
+ *.h5 filter=lfs diff=lfs merge=lfs -text
5
+ *.tflite filter=lfs diff=lfs merge=lfs -text
6
+ *.tar.gz filter=lfs diff=lfs merge=lfs -text
7
+ *.ot filter=lfs diff=lfs merge=lfs -text
8
+ *.onnx filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,40 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ language: en
3
+ tags:
4
+ - deberta-v1
5
+ - fill-mask
6
+ thumbnail: https://huggingface.co/front/thumbnails/microsoft.png
7
+ license: mit
8
+ ---
9
+
10
+ ## DeBERTa: Decoding-enhanced BERT with Disentangled Attention
11
+
12
+ [DeBERTa](https://arxiv.org/abs/2006.03654) improves the BERT and RoBERTa models using disentangled attention and enhanced mask decoder. It outperforms BERT and RoBERTa on majority of NLU tasks with 80GB training data.
13
+
14
+ Please check the [official repository](https://github.com/microsoft/DeBERTa) for more details and updates.
15
+
16
+
17
+ #### Fine-tuning on NLU tasks
18
+
19
+ We present the dev results on SQuAD 1.1/2.0 and MNLI tasks.
20
+
21
+ | Model | SQuAD 1.1 | SQuAD 2.0 | MNLI-m |
22
+ |-------------------|-----------|-----------|--------|
23
+ | RoBERTa-base | 91.5/84.6 | 83.7/80.5 | 87.6 |
24
+ | XLNet-Large | -/- | -/80.2 | 86.8 |
25
+ | **DeBERTa-base** | 93.1/87.2 | 86.2/83.1 | 88.8 |
26
+
27
+ ### Citation
28
+
29
+ If you find DeBERTa useful for your work, please cite the following paper:
30
+
31
+ ``` latex
32
+ @inproceedings{
33
+ he2021deberta,
34
+ title={DEBERTA: DECODING-ENHANCED BERT WITH DISENTANGLED ATTENTION},
35
+ author={Pengcheng He and Xiaodong Liu and Jianfeng Gao and Weizhu Chen},
36
+ booktitle={International Conference on Learning Representations},
37
+ year={2021},
38
+ url={https://openreview.net/forum?id=XPZIaotutsD}
39
+ }
40
+ ```
bpe_encoder.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e7c6f9eecb461c01e09c00656ccf3e27944b9e74bfe29e51632b13d3cd9d6c8e
3
+ size 3917897
config.json ADDED
@@ -0,0 +1,19 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "model_type": "deberta",
3
+ "attention_probs_dropout_prob": 0.1,
4
+ "hidden_act": "gelu",
5
+ "hidden_dropout_prob": 0.1,
6
+ "hidden_size": 768,
7
+ "initializer_range": 0.02,
8
+ "intermediate_size": 3072,
9
+ "max_position_embeddings": 512,
10
+ "relative_attention": true,
11
+ "pos_att_type": "c2p|p2c",
12
+ "layer_norm_eps": 1e-7,
13
+ "max_relative_positions": -1,
14
+ "position_biased_input": false,
15
+ "num_attention_heads": 12,
16
+ "num_hidden_layers": 12,
17
+ "type_vocab_size": 0,
18
+ "vocab_size": 50265
19
+ }
merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
pytorch_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:81ab61c5dc9111f81e528b7b3ae93997f4ae72ba531e60587835be894ab0ffe5
3
+ size 558614189
rust_model.ot ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:42a8937bf8d3d98be44be18d92c0fafdebcddf839c8be2d72e18ec1b408b1e3c
3
+ size 558613749
tf_model.h5 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:16442fa0caaa8927e020e212b89b354db00a85f06c9b68eda20815233f619414
3
+ size 554669920
tokenizer_config.json ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {
2
+ "do_lower_case": false,
3
+ "vocab_type": "gpt2"
4
+ }
vocab.json ADDED
The diff for this file is too large to render. See raw diff