Add SetFit model
Browse files- 1_Pooling/config.json +7 -0
- README.md +214 -0
- config.json +24 -0
- config_sentence_transformers.json +7 -0
- config_setfit.json +4 -0
- model.safetensors +3 -0
- model_head.pkl +3 -0
- modules.json +14 -0
- sentence_bert_config.json +4 -0
- special_tokens_map.json +51 -0
- tokenizer.json +0 -0
- tokenizer_config.json +59 -0
- vocab.txt +0 -0
1_Pooling/config.json
ADDED
|
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"word_embedding_dimension": 768,
|
| 3 |
+
"pooling_mode_cls_token": false,
|
| 4 |
+
"pooling_mode_mean_tokens": true,
|
| 5 |
+
"pooling_mode_max_tokens": false,
|
| 6 |
+
"pooling_mode_mean_sqrt_len_tokens": false
|
| 7 |
+
}
|
README.md
ADDED
|
@@ -0,0 +1,214 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
library_name: setfit
|
| 3 |
+
tags:
|
| 4 |
+
- setfit
|
| 5 |
+
- sentence-transformers
|
| 6 |
+
- text-classification
|
| 7 |
+
- generated_from_setfit_trainer
|
| 8 |
+
metrics:
|
| 9 |
+
- accuracy
|
| 10 |
+
widget:
|
| 11 |
+
- text: Buses are more simple - you just buy a ticket .
|
| 12 |
+
- text: As citizens of village , we totally care about environment of our village
|
| 13 |
+
.
|
| 14 |
+
- text: So , finally I suggest that it would be a great idea to combine the different
|
| 15 |
+
types of activities , both popular and the newest .
|
| 16 |
+
- text: Had 12 years old .
|
| 17 |
+
- text: On the other hand , I have the theoretical knowledge to use new the technologies
|
| 18 |
+
this great project requires .
|
| 19 |
+
pipeline_tag: text-classification
|
| 20 |
+
inference: true
|
| 21 |
+
base_model: sentence-transformers/paraphrase-mpnet-base-v2
|
| 22 |
+
model-index:
|
| 23 |
+
- name: SetFit with sentence-transformers/paraphrase-mpnet-base-v2
|
| 24 |
+
results:
|
| 25 |
+
- task:
|
| 26 |
+
type: text-classification
|
| 27 |
+
name: Text Classification
|
| 28 |
+
dataset:
|
| 29 |
+
name: Unknown
|
| 30 |
+
type: unknown
|
| 31 |
+
split: test
|
| 32 |
+
metrics:
|
| 33 |
+
- type: accuracy
|
| 34 |
+
value: 0.13152173913043477
|
| 35 |
+
name: Accuracy
|
| 36 |
+
---
|
| 37 |
+
|
| 38 |
+
# SetFit with sentence-transformers/paraphrase-mpnet-base-v2
|
| 39 |
+
|
| 40 |
+
This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [sentence-transformers/paraphrase-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2) as the Sentence Transformer embedding model. A [SetFitHead](huggingface.co/docs/setfit/reference/main#setfit.SetFitHead) instance is used for classification.
|
| 41 |
+
|
| 42 |
+
The model has been trained using an efficient few-shot learning technique that involves:
|
| 43 |
+
|
| 44 |
+
1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.
|
| 45 |
+
2. Training a classification head with features from the fine-tuned Sentence Transformer.
|
| 46 |
+
|
| 47 |
+
## Model Details
|
| 48 |
+
|
| 49 |
+
### Model Description
|
| 50 |
+
- **Model Type:** SetFit
|
| 51 |
+
- **Sentence Transformer body:** [sentence-transformers/paraphrase-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2)
|
| 52 |
+
- **Classification head:** a [SetFitHead](huggingface.co/docs/setfit/reference/main#setfit.SetFitHead) instance
|
| 53 |
+
- **Maximum Sequence Length:** 512 tokens
|
| 54 |
+
- **Number of Classes:** 8 classes
|
| 55 |
+
<!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
|
| 56 |
+
<!-- - **Language:** Unknown -->
|
| 57 |
+
<!-- - **License:** Unknown -->
|
| 58 |
+
|
| 59 |
+
### Model Sources
|
| 60 |
+
|
| 61 |
+
- **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit)
|
| 62 |
+
- **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055)
|
| 63 |
+
- **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)
|
| 64 |
+
|
| 65 |
+
### Model Labels
|
| 66 |
+
| Label | Examples |
|
| 67 |
+
|:------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|
| 68 |
+
| 7 | <ul><li>"When I 've had a very bad and stressful day I can relax doing karate , because It 's the kind of sport that it is n't very hard ."</li><li>"Also , you 'll meet friendly people who usually ask to you something to be friends and change your telephone number ."</li><li>'When I have spare time , I often gather my friends to watch basketball match on television .'</li></ul> |
|
| 69 |
+
| 4 | <ul><li>"stop shouting . do n't shout ."</li><li>'Yours Sincerely .'</li><li>'Something that they don know was that the whole thing was a movie !'</li></ul> |
|
| 70 |
+
| 1 | <ul><li>'She stay sleeping in the bed and doing nothing all day .'</li><li>'People collects trash of their house and await the trash truck that carried the trash to a landfill located outside the village .'</li><li>"Travelling by car is n't so much more convenient unless it is so much more comfortable , but actually we do n't think about the contamination in our planet ."</li></ul> |
|
| 71 |
+
| 6 | <ul><li>'When the concert finished , we went to cloakroom to get signatures from musicians .'</li><li>'We have solar panels and a place to make compost at the last garden , with worms who eat and degrade all the organic waste of the school .'</li><li>'The aim of this report is to give you my personal point of view of the course I did in your branch in Madrid last month .'</li></ul> |
|
| 72 |
+
| 5 | <ul><li>'You can also bought a lot of gifts like key chains , statue , or what else memories to be made before returning to Malaysia .'</li><li>'I always said that I passed that test and I was sure of that .'</li><li>'In addition , to decrease the risk of negative comments or posts , Facebook and Twitter would improve their futures to solve the less personal privacy problem .'</li></ul> |
|
| 73 |
+
| 2 | <ul><li>'They were not only really clever people but also excellent co - workers .'</li><li>'On balance , learning foreign languages is very positive on different aspect , so if you have the positivity of learning a new language do it , because it will bring you many benefits .'</li><li>'In many years of work I have honed my skills in managing non - standard situations , analyzing the problem , finding and implementing practical and easy solutions .'</li></ul> |
|
| 74 |
+
| 0 | <ul><li>'It is very funny .'</li><li>'In China , English is took to be a foreign language which many students choose to learn .'</li><li>'We also value that they have specialised studies in Cloud technology , and hosting management .'</li></ul> |
|
| 75 |
+
| 3 | <ul><li>"Usually there are generation problems , sons do n't understand parents and vicecersa , but dialoging and listening emotions and facts , everyone can have another point of view ."</li><li>'the two boys heard that he was planing to steal some money and kill people so the boys start their adventure on stoping Injuin Joe ...'</li><li>'As an example , if you are able to get alone with your travel companion could enjoy each moment of the trip , exchange some pictures , eat together , and visit places with common interest such as museums or malls .'</li></ul> |
|
| 76 |
+
|
| 77 |
+
## Evaluation
|
| 78 |
+
|
| 79 |
+
### Metrics
|
| 80 |
+
| Label | Accuracy |
|
| 81 |
+
|:--------|:---------|
|
| 82 |
+
| **all** | 0.1315 |
|
| 83 |
+
|
| 84 |
+
## Uses
|
| 85 |
+
|
| 86 |
+
### Direct Use for Inference
|
| 87 |
+
|
| 88 |
+
First install the SetFit library:
|
| 89 |
+
|
| 90 |
+
```bash
|
| 91 |
+
pip install setfit
|
| 92 |
+
```
|
| 93 |
+
|
| 94 |
+
Then you can load this model and run inference.
|
| 95 |
+
|
| 96 |
+
```python
|
| 97 |
+
from setfit import SetFitModel
|
| 98 |
+
|
| 99 |
+
# Download from the 🤗 Hub
|
| 100 |
+
model = SetFitModel.from_pretrained("HelgeKn/BEA2019-multi-class-4")
|
| 101 |
+
# Run inference
|
| 102 |
+
preds = model("Had 12 years old .")
|
| 103 |
+
```
|
| 104 |
+
|
| 105 |
+
<!--
|
| 106 |
+
### Downstream Use
|
| 107 |
+
|
| 108 |
+
*List how someone could finetune this model on their own dataset.*
|
| 109 |
+
-->
|
| 110 |
+
|
| 111 |
+
<!--
|
| 112 |
+
### Out-of-Scope Use
|
| 113 |
+
|
| 114 |
+
*List how the model may foreseeably be misused and address what users ought not to do with the model.*
|
| 115 |
+
-->
|
| 116 |
+
|
| 117 |
+
<!--
|
| 118 |
+
## Bias, Risks and Limitations
|
| 119 |
+
|
| 120 |
+
*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
|
| 121 |
+
-->
|
| 122 |
+
|
| 123 |
+
<!--
|
| 124 |
+
### Recommendations
|
| 125 |
+
|
| 126 |
+
*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
|
| 127 |
+
-->
|
| 128 |
+
|
| 129 |
+
## Training Details
|
| 130 |
+
|
| 131 |
+
### Training Set Metrics
|
| 132 |
+
| Training set | Min | Median | Max |
|
| 133 |
+
|:-------------|:----|:--------|:----|
|
| 134 |
+
| Word count | 3 | 19.1562 | 42 |
|
| 135 |
+
|
| 136 |
+
| Label | Training Sample Count |
|
| 137 |
+
|:------|:----------------------|
|
| 138 |
+
| 0 | 4 |
|
| 139 |
+
| 1 | 4 |
|
| 140 |
+
| 2 | 4 |
|
| 141 |
+
| 3 | 4 |
|
| 142 |
+
| 4 | 4 |
|
| 143 |
+
| 5 | 4 |
|
| 144 |
+
| 6 | 4 |
|
| 145 |
+
| 7 | 4 |
|
| 146 |
+
|
| 147 |
+
### Training Hyperparameters
|
| 148 |
+
- batch_size: (16, 16)
|
| 149 |
+
- num_epochs: (2, 2)
|
| 150 |
+
- max_steps: -1
|
| 151 |
+
- sampling_strategy: oversampling
|
| 152 |
+
- num_iterations: 20
|
| 153 |
+
- body_learning_rate: (2e-05, 2e-05)
|
| 154 |
+
- head_learning_rate: 2e-05
|
| 155 |
+
- loss: CosineSimilarityLoss
|
| 156 |
+
- distance_metric: cosine_distance
|
| 157 |
+
- margin: 0.25
|
| 158 |
+
- end_to_end: False
|
| 159 |
+
- use_amp: False
|
| 160 |
+
- warmup_proportion: 0.1
|
| 161 |
+
- seed: 42
|
| 162 |
+
- eval_max_steps: -1
|
| 163 |
+
- load_best_model_at_end: False
|
| 164 |
+
|
| 165 |
+
### Training Results
|
| 166 |
+
| Epoch | Step | Training Loss | Validation Loss |
|
| 167 |
+
|:------:|:----:|:-------------:|:---------------:|
|
| 168 |
+
| 0.0125 | 1 | 0.1886 | - |
|
| 169 |
+
| 0.625 | 50 | 0.0778 | - |
|
| 170 |
+
| 1.25 | 100 | 0.0194 | - |
|
| 171 |
+
| 1.875 | 150 | 0.0069 | - |
|
| 172 |
+
|
| 173 |
+
### Framework Versions
|
| 174 |
+
- Python: 3.9.13
|
| 175 |
+
- SetFit: 1.0.1
|
| 176 |
+
- Sentence Transformers: 2.2.2
|
| 177 |
+
- Transformers: 4.36.0
|
| 178 |
+
- PyTorch: 2.1.1+cpu
|
| 179 |
+
- Datasets: 2.15.0
|
| 180 |
+
- Tokenizers: 0.15.0
|
| 181 |
+
|
| 182 |
+
## Citation
|
| 183 |
+
|
| 184 |
+
### BibTeX
|
| 185 |
+
```bibtex
|
| 186 |
+
@article{https://doi.org/10.48550/arxiv.2209.11055,
|
| 187 |
+
doi = {10.48550/ARXIV.2209.11055},
|
| 188 |
+
url = {https://arxiv.org/abs/2209.11055},
|
| 189 |
+
author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
|
| 190 |
+
keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
|
| 191 |
+
title = {Efficient Few-Shot Learning Without Prompts},
|
| 192 |
+
publisher = {arXiv},
|
| 193 |
+
year = {2022},
|
| 194 |
+
copyright = {Creative Commons Attribution 4.0 International}
|
| 195 |
+
}
|
| 196 |
+
```
|
| 197 |
+
|
| 198 |
+
<!--
|
| 199 |
+
## Glossary
|
| 200 |
+
|
| 201 |
+
*Clearly define terms in order to be accessible across audiences.*
|
| 202 |
+
-->
|
| 203 |
+
|
| 204 |
+
<!--
|
| 205 |
+
## Model Card Authors
|
| 206 |
+
|
| 207 |
+
*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
|
| 208 |
+
-->
|
| 209 |
+
|
| 210 |
+
<!--
|
| 211 |
+
## Model Card Contact
|
| 212 |
+
|
| 213 |
+
*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
|
| 214 |
+
-->
|
config.json
ADDED
|
@@ -0,0 +1,24 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_name_or_path": "C:\\Users\\Man_f/.cache\\torch\\sentence_transformers\\sentence-transformers_paraphrase-mpnet-base-v2\\",
|
| 3 |
+
"architectures": [
|
| 4 |
+
"MPNetModel"
|
| 5 |
+
],
|
| 6 |
+
"attention_probs_dropout_prob": 0.1,
|
| 7 |
+
"bos_token_id": 0,
|
| 8 |
+
"eos_token_id": 2,
|
| 9 |
+
"hidden_act": "gelu",
|
| 10 |
+
"hidden_dropout_prob": 0.1,
|
| 11 |
+
"hidden_size": 768,
|
| 12 |
+
"initializer_range": 0.02,
|
| 13 |
+
"intermediate_size": 3072,
|
| 14 |
+
"layer_norm_eps": 1e-05,
|
| 15 |
+
"max_position_embeddings": 514,
|
| 16 |
+
"model_type": "mpnet",
|
| 17 |
+
"num_attention_heads": 12,
|
| 18 |
+
"num_hidden_layers": 12,
|
| 19 |
+
"pad_token_id": 1,
|
| 20 |
+
"relative_attention_num_buckets": 32,
|
| 21 |
+
"torch_dtype": "float32",
|
| 22 |
+
"transformers_version": "4.36.0",
|
| 23 |
+
"vocab_size": 30527
|
| 24 |
+
}
|
config_sentence_transformers.json
ADDED
|
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"__version__": {
|
| 3 |
+
"sentence_transformers": "2.0.0",
|
| 4 |
+
"transformers": "4.7.0",
|
| 5 |
+
"pytorch": "1.9.0+cu102"
|
| 6 |
+
}
|
| 7 |
+
}
|
config_setfit.json
ADDED
|
@@ -0,0 +1,4 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"labels": null,
|
| 3 |
+
"normalize_embeddings": false
|
| 4 |
+
}
|
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:7bba2812186f482f6848093fe2fc50cae5c0554b1d77ad023b8a1298602513f9
|
| 3 |
+
size 437967672
|
model_head.pkl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:56eec723acfc91ef2ea01c5615a43f3d34a85d5a15627ac583ca5fbec40a4533
|
| 3 |
+
size 26128
|
modules.json
ADDED
|
@@ -0,0 +1,14 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
[
|
| 2 |
+
{
|
| 3 |
+
"idx": 0,
|
| 4 |
+
"name": "0",
|
| 5 |
+
"path": "",
|
| 6 |
+
"type": "sentence_transformers.models.Transformer"
|
| 7 |
+
},
|
| 8 |
+
{
|
| 9 |
+
"idx": 1,
|
| 10 |
+
"name": "1",
|
| 11 |
+
"path": "1_Pooling",
|
| 12 |
+
"type": "sentence_transformers.models.Pooling"
|
| 13 |
+
}
|
| 14 |
+
]
|
sentence_bert_config.json
ADDED
|
@@ -0,0 +1,4 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"max_seq_length": 512,
|
| 3 |
+
"do_lower_case": false
|
| 4 |
+
}
|
special_tokens_map.json
ADDED
|
@@ -0,0 +1,51 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"bos_token": {
|
| 3 |
+
"content": "<s>",
|
| 4 |
+
"lstrip": false,
|
| 5 |
+
"normalized": false,
|
| 6 |
+
"rstrip": false,
|
| 7 |
+
"single_word": false
|
| 8 |
+
},
|
| 9 |
+
"cls_token": {
|
| 10 |
+
"content": "<s>",
|
| 11 |
+
"lstrip": false,
|
| 12 |
+
"normalized": true,
|
| 13 |
+
"rstrip": false,
|
| 14 |
+
"single_word": false
|
| 15 |
+
},
|
| 16 |
+
"eos_token": {
|
| 17 |
+
"content": "</s>",
|
| 18 |
+
"lstrip": false,
|
| 19 |
+
"normalized": false,
|
| 20 |
+
"rstrip": false,
|
| 21 |
+
"single_word": false
|
| 22 |
+
},
|
| 23 |
+
"mask_token": {
|
| 24 |
+
"content": "<mask>",
|
| 25 |
+
"lstrip": true,
|
| 26 |
+
"normalized": false,
|
| 27 |
+
"rstrip": false,
|
| 28 |
+
"single_word": false
|
| 29 |
+
},
|
| 30 |
+
"pad_token": {
|
| 31 |
+
"content": "<pad>",
|
| 32 |
+
"lstrip": false,
|
| 33 |
+
"normalized": false,
|
| 34 |
+
"rstrip": false,
|
| 35 |
+
"single_word": false
|
| 36 |
+
},
|
| 37 |
+
"sep_token": {
|
| 38 |
+
"content": "</s>",
|
| 39 |
+
"lstrip": false,
|
| 40 |
+
"normalized": true,
|
| 41 |
+
"rstrip": false,
|
| 42 |
+
"single_word": false
|
| 43 |
+
},
|
| 44 |
+
"unk_token": {
|
| 45 |
+
"content": "[UNK]",
|
| 46 |
+
"lstrip": false,
|
| 47 |
+
"normalized": false,
|
| 48 |
+
"rstrip": false,
|
| 49 |
+
"single_word": false
|
| 50 |
+
}
|
| 51 |
+
}
|
tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,59 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"added_tokens_decoder": {
|
| 3 |
+
"0": {
|
| 4 |
+
"content": "<s>",
|
| 5 |
+
"lstrip": false,
|
| 6 |
+
"normalized": false,
|
| 7 |
+
"rstrip": false,
|
| 8 |
+
"single_word": false,
|
| 9 |
+
"special": true
|
| 10 |
+
},
|
| 11 |
+
"1": {
|
| 12 |
+
"content": "<pad>",
|
| 13 |
+
"lstrip": false,
|
| 14 |
+
"normalized": false,
|
| 15 |
+
"rstrip": false,
|
| 16 |
+
"single_word": false,
|
| 17 |
+
"special": true
|
| 18 |
+
},
|
| 19 |
+
"2": {
|
| 20 |
+
"content": "</s>",
|
| 21 |
+
"lstrip": false,
|
| 22 |
+
"normalized": false,
|
| 23 |
+
"rstrip": false,
|
| 24 |
+
"single_word": false,
|
| 25 |
+
"special": true
|
| 26 |
+
},
|
| 27 |
+
"104": {
|
| 28 |
+
"content": "[UNK]",
|
| 29 |
+
"lstrip": false,
|
| 30 |
+
"normalized": false,
|
| 31 |
+
"rstrip": false,
|
| 32 |
+
"single_word": false,
|
| 33 |
+
"special": true
|
| 34 |
+
},
|
| 35 |
+
"30526": {
|
| 36 |
+
"content": "<mask>",
|
| 37 |
+
"lstrip": true,
|
| 38 |
+
"normalized": false,
|
| 39 |
+
"rstrip": false,
|
| 40 |
+
"single_word": false,
|
| 41 |
+
"special": true
|
| 42 |
+
}
|
| 43 |
+
},
|
| 44 |
+
"bos_token": "<s>",
|
| 45 |
+
"clean_up_tokenization_spaces": true,
|
| 46 |
+
"cls_token": "<s>",
|
| 47 |
+
"do_basic_tokenize": true,
|
| 48 |
+
"do_lower_case": true,
|
| 49 |
+
"eos_token": "</s>",
|
| 50 |
+
"mask_token": "<mask>",
|
| 51 |
+
"model_max_length": 512,
|
| 52 |
+
"never_split": null,
|
| 53 |
+
"pad_token": "<pad>",
|
| 54 |
+
"sep_token": "</s>",
|
| 55 |
+
"strip_accents": null,
|
| 56 |
+
"tokenize_chinese_chars": true,
|
| 57 |
+
"tokenizer_class": "MPNetTokenizer",
|
| 58 |
+
"unk_token": "[UNK]"
|
| 59 |
+
}
|
vocab.txt
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|