Upload folder using huggingface_hub
Browse files- 1_Pooling/config.json +10 -0
- README.md +336 -0
- config.json +24 -0
- config_sentence_transformers.json +10 -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 +37 -0
- tokenizer.json +0 -0
- tokenizer_config.json +56 -0
- vocab.txt +0 -0
1_Pooling/config.json
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{
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"word_embedding_dimension": 768,
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"pooling_mode_cls_token": false,
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"pooling_mode_mean_tokens": true,
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"pooling_mode_max_tokens": false,
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"pooling_mode_mean_sqrt_len_tokens": false,
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"pooling_mode_weightedmean_tokens": false,
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"pooling_mode_lasttoken": false,
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"include_prompt": true
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}
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README.md
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1 |
+
---
|
2 |
+
tags:
|
3 |
+
- setfit
|
4 |
+
- sentence-transformers
|
5 |
+
- text-classification
|
6 |
+
- generated_from_setfit_trainer
|
7 |
+
widget:
|
8 |
+
- text: 46 Abs. 2 BGG zum Beispiel die Schuldneranweisung gemäss den Bestimmungen
|
9 |
+
zum Schutz der ehelichen Gemeinschaft (Art. 177 ZGB; BGE 134 III 667), die Einsprache
|
10 |
+
gegen die Ausstellung einer Erbenbescheinigung (Art. 559 Abs. 1 ZGB; Urteil 5A_162/2007
|
11 |
+
vom 16. Juli 2007 E. 5.2) oder das Inventar über das Kindesvermögen (Art. 318
|
12 |
+
Abs. 2 ZGB; Urteil 5A_169/2007 vom 21. Juni 2007 E. 3).
|
13 |
+
- text: Im OP der Kinderklinik der MHH werden pro Jahr zwischen 1500 und 2000 Operationen
|
14 |
+
durchgeführt.
|
15 |
+
- text: Die Bindungen sollten anfangs in Fahrtrichtung zeigen.
|
16 |
+
- text: Raumausstatter gesucht, Recklinghausen
|
17 |
+
- text: Mehr Leistung durch Selbstgespräche
|
18 |
+
metrics:
|
19 |
+
- accuracy
|
20 |
+
pipeline_tag: text-classification
|
21 |
+
library_name: setfit
|
22 |
+
inference: false
|
23 |
+
---
|
24 |
+
|
25 |
+
# SetFit
|
26 |
+
|
27 |
+
This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. A [SetFitHead](huggingface.co/docs/setfit/reference/main#setfit.SetFitHead) instance is used for classification.
|
28 |
+
|
29 |
+
The model has been trained using an efficient few-shot learning technique that involves:
|
30 |
+
|
31 |
+
1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.
|
32 |
+
2. Training a classification head with features from the fine-tuned Sentence Transformer.
|
33 |
+
|
34 |
+
## Model Details
|
35 |
+
|
36 |
+
### Model Description
|
37 |
+
- **Model Type:** SetFit
|
38 |
+
<!-- - **Sentence Transformer:** [Unknown](https://huggingface.co/unknown) -->
|
39 |
+
- **Classification head:** a [SetFitHead](huggingface.co/docs/setfit/reference/main#setfit.SetFitHead) instance
|
40 |
+
- **Maximum Sequence Length:** 512 tokens
|
41 |
+
<!-- - **Number of Classes:** Unknown -->
|
42 |
+
<!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
|
43 |
+
<!-- - **Language:** Unknown -->
|
44 |
+
<!-- - **License:** Unknown -->
|
45 |
+
|
46 |
+
### Model Sources
|
47 |
+
|
48 |
+
- **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit)
|
49 |
+
- **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055)
|
50 |
+
- **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)
|
51 |
+
|
52 |
+
## Uses
|
53 |
+
|
54 |
+
### Direct Use for Inference
|
55 |
+
|
56 |
+
First install the SetFit library:
|
57 |
+
|
58 |
+
```bash
|
59 |
+
pip install setfit
|
60 |
+
```
|
61 |
+
|
62 |
+
Then you can load this model and run inference.
|
63 |
+
|
64 |
+
```python
|
65 |
+
from setfit import SetFitModel
|
66 |
+
|
67 |
+
# Download from the 🤗 Hub
|
68 |
+
model = SetFitModel.from_pretrained("setfit_model_id")
|
69 |
+
# Run inference
|
70 |
+
preds = model("Mehr Leistung durch Selbstgespräche")
|
71 |
+
```
|
72 |
+
|
73 |
+
<!--
|
74 |
+
### Downstream Use
|
75 |
+
|
76 |
+
*List how someone could finetune this model on their own dataset.*
|
77 |
+
-->
|
78 |
+
|
79 |
+
<!--
|
80 |
+
### Out-of-Scope Use
|
81 |
+
|
82 |
+
*List how the model may foreseeably be misused and address what users ought not to do with the model.*
|
83 |
+
-->
|
84 |
+
|
85 |
+
<!--
|
86 |
+
## Bias, Risks and Limitations
|
87 |
+
|
88 |
+
*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
|
89 |
+
-->
|
90 |
+
|
91 |
+
<!--
|
92 |
+
### Recommendations
|
93 |
+
|
94 |
+
*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
|
95 |
+
-->
|
96 |
+
|
97 |
+
## Training Details
|
98 |
+
|
99 |
+
### Training Set Metrics
|
100 |
+
| Training set | Min | Median | Max |
|
101 |
+
|:-------------|:----|:--------|:----|
|
102 |
+
| Word count | 1 | 16.7450 | 201 |
|
103 |
+
|
104 |
+
### Training Hyperparameters
|
105 |
+
- batch_size: (16, 32)
|
106 |
+
- num_epochs: (2, 32)
|
107 |
+
- max_steps: -1
|
108 |
+
- sampling_strategy: oversampling
|
109 |
+
- body_learning_rate: (2e-05, 1e-05)
|
110 |
+
- head_learning_rate: 0.01
|
111 |
+
- loss: CoSENTLoss
|
112 |
+
- distance_metric: cosine_distance
|
113 |
+
- margin: 0.25
|
114 |
+
- end_to_end: True
|
115 |
+
- use_amp: False
|
116 |
+
- warmup_proportion: 0.1
|
117 |
+
- l2_weight: 0.01
|
118 |
+
- max_length: 512
|
119 |
+
- seed: 13579
|
120 |
+
- eval_max_steps: -1
|
121 |
+
- load_best_model_at_end: False
|
122 |
+
|
123 |
+
### Training Results
|
124 |
+
| Epoch | Step | Training Loss | Validation Loss |
|
125 |
+
|:------:|:-----:|:-------------:|:---------------:|
|
126 |
+
| 0.0001 | 1 | 3.2672 | - |
|
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| 0.0119 | 100 | 5.7496 | - |
|
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| 0.0239 | 200 | 4.7559 | - |
|
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| 0.0358 | 300 | 4.2203 | - |
|
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| 0.0477 | 400 | 4.0467 | - |
|
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| 0.0596 | 500 | 3.9136 | - |
|
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| 0.0716 | 600 | 3.791 | - |
|
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| 0.0835 | 700 | 3.6316 | - |
|
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| 0.0954 | 800 | 3.4742 | - |
|
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| 0.1073 | 900 | 3.1001 | - |
|
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| 0.1193 | 1000 | 2.4123 | - |
|
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| 0.1312 | 1100 | 1.9843 | - |
|
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| 0.1431 | 1200 | 1.9276 | - |
|
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| 0.1551 | 1300 | 2.5268 | - |
|
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| 0.1670 | 1400 | 2.229 | - |
|
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| 0.1789 | 1500 | 2.0492 | - |
|
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| 0.1908 | 1600 | 1.9396 | - |
|
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| 0.2028 | 1700 | 1.6849 | - |
|
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| 0.2147 | 1800 | 1.9385 | - |
|
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| 0.2266 | 1900 | 1.6651 | - |
|
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| 0.2385 | 2000 | 1.011 | - |
|
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| 0.2505 | 2100 | 1.3135 | - |
|
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| 0.2624 | 2200 | 1.347 | - |
|
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| 0.2743 | 2300 | 1.4244 | - |
|
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| 0.2863 | 2400 | 1.0954 | - |
|
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| 0.2982 | 2500 | 0.9091 | - |
|
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| 0.3101 | 2600 | 1.0739 | - |
|
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| 0.3220 | 2700 | 0.9281 | - |
|
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| 0.3340 | 2800 | 0.7909 | - |
|
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| 0.3459 | 2900 | 0.5911 | - |
|
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| 0.3578 | 3000 | 0.476 | - |
|
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| 0.3698 | 3100 | 0.5782 | - |
|
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| 0.3817 | 3200 | 0.4535 | - |
|
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| 0.3936 | 3300 | 0.371 | - |
|
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| 0.4055 | 3400 | 0.3692 | - |
|
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| 0.4175 | 3500 | 0.2393 | - |
|
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| 0.4294 | 3600 | 0.2623 | - |
|
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| 0.4413 | 3700 | 0.2643 | - |
|
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| 0.4532 | 3800 | 0.3065 | - |
|
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| 0.4652 | 3900 | 0.2552 | - |
|
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| 0.4771 | 4000 | 0.2093 | - |
|
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| 0.4890 | 4100 | 0.217 | - |
|
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| 0.5010 | 4200 | 0.1981 | - |
|
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| 0.5129 | 4300 | 0.0827 | - |
|
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| 0.5248 | 4400 | 0.1562 | - |
|
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+
| 0.5367 | 4500 | 0.0438 | - |
|
172 |
+
| 0.5487 | 4600 | 0.0976 | - |
|
173 |
+
| 0.5606 | 4700 | 0.0307 | - |
|
174 |
+
| 0.5725 | 4800 | 0.0584 | - |
|
175 |
+
| 0.5844 | 4900 | 0.0503 | - |
|
176 |
+
| 0.5964 | 5000 | 0.0342 | - |
|
177 |
+
| 0.6083 | 5100 | 0.0244 | - |
|
178 |
+
| 0.6202 | 5200 | 0.0474 | - |
|
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| 0.6322 | 5300 | 0.0346 | - |
|
180 |
+
| 0.6441 | 5400 | 0.0128 | - |
|
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+
| 0.6560 | 5500 | 0.0077 | - |
|
182 |
+
| 0.6679 | 5600 | 0.0303 | - |
|
183 |
+
| 0.6799 | 5700 | 0.097 | - |
|
184 |
+
| 0.6918 | 5800 | 0.0152 | - |
|
185 |
+
| 0.7037 | 5900 | 0.0135 | - |
|
186 |
+
| 0.7156 | 6000 | 0.0222 | - |
|
187 |
+
| 0.7276 | 6100 | 0.0092 | - |
|
188 |
+
| 0.7395 | 6200 | 0.0277 | - |
|
189 |
+
| 0.7514 | 6300 | 0.0179 | - |
|
190 |
+
| 0.7634 | 6400 | 0.0092 | - |
|
191 |
+
| 0.7753 | 6500 | 0.0064 | - |
|
192 |
+
| 0.7872 | 6600 | 0.0176 | - |
|
193 |
+
| 0.7991 | 6700 | 0.0126 | - |
|
194 |
+
| 0.8111 | 6800 | 0.022 | - |
|
195 |
+
| 0.8230 | 6900 | 0.0187 | - |
|
196 |
+
| 0.8349 | 7000 | 0.0062 | - |
|
197 |
+
| 0.8469 | 7100 | 0.0031 | - |
|
198 |
+
| 0.8588 | 7200 | 0.0313 | - |
|
199 |
+
| 0.8707 | 7300 | 0.0026 | - |
|
200 |
+
| 0.8826 | 7400 | 0.0063 | - |
|
201 |
+
| 0.8946 | 7500 | 0.0008 | - |
|
202 |
+
| 0.9065 | 7600 | 0.0039 | - |
|
203 |
+
| 0.9184 | 7700 | 0.0009 | - |
|
204 |
+
| 0.9303 | 7800 | 0.001 | - |
|
205 |
+
| 0.9423 | 7900 | 0.0027 | - |
|
206 |
+
| 0.9542 | 8000 | 0.0023 | - |
|
207 |
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| 0.9661 | 8100 | 0.0027 | - |
|
208 |
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| 0.9781 | 8200 | 0.0022 | - |
|
209 |
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| 0.9900 | 8300 | 0.0238 | - |
|
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| 1.0019 | 8400 | 0.0008 | - |
|
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| 1.0138 | 8500 | 0.0104 | - |
|
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| 1.0258 | 8600 | 0.0014 | - |
|
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| 1.0377 | 8700 | 0.0129 | - |
|
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| 1.0496 | 8800 | 0.0014 | - |
|
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| 1.0615 | 8900 | 0.002 | - |
|
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| 1.0735 | 9000 | 0.0013 | - |
|
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| 1.0854 | 9100 | 0.0046 | - |
|
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| 1.0973 | 9200 | 0.0023 | - |
|
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| 1.1093 | 9300 | 0.0023 | - |
|
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| 1.1212 | 9400 | 0.0027 | - |
|
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| 1.1331 | 9500 | 0.0021 | - |
|
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| 1.1450 | 9600 | 0.0014 | - |
|
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| 1.1570 | 9700 | 0.0036 | - |
|
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| 1.1689 | 9800 | 0.0011 | - |
|
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| 1.1808 | 9900 | 0.0027 | - |
|
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| 1.1927 | 10000 | 0.0013 | - |
|
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| 1.2047 | 10100 | 0.0007 | - |
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| 1.2166 | 10200 | 0.0012 | - |
|
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| 1.2285 | 10300 | 0.0033 | - |
|
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| 1.2405 | 10400 | 0.0013 | - |
|
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| 1.2524 | 10500 | 0.0008 | - |
|
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| 1.2643 | 10600 | 0.0011 | - |
|
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| 1.2762 | 10700 | 0.0007 | - |
|
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| 1.2882 | 10800 | 0.0008 | - |
|
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| 1.3001 | 10900 | 0.0005 | - |
|
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| 1.3120 | 11000 | 0.0007 | - |
|
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| 1.3240 | 11100 | 0.0015 | - |
|
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| 1.3359 | 11200 | 0.0005 | - |
|
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| 1.3478 | 11300 | 0.0011 | - |
|
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| 1.3597 | 11400 | 0.001 | - |
|
241 |
+
| 1.3717 | 11500 | 0.0004 | - |
|
242 |
+
| 1.3836 | 11600 | 0.0015 | - |
|
243 |
+
| 1.3955 | 11700 | 0.0007 | - |
|
244 |
+
| 1.4074 | 11800 | 0.0007 | - |
|
245 |
+
| 1.4194 | 11900 | 0.0021 | - |
|
246 |
+
| 1.4313 | 12000 | 0.0004 | - |
|
247 |
+
| 1.4432 | 12100 | 0.0005 | - |
|
248 |
+
| 1.4552 | 12200 | 0.0007 | - |
|
249 |
+
| 1.4671 | 12300 | 0.0007 | - |
|
250 |
+
| 1.4790 | 12400 | 0.0015 | - |
|
251 |
+
| 1.4909 | 12500 | 0.0007 | - |
|
252 |
+
| 1.5029 | 12600 | 0.0004 | - |
|
253 |
+
| 1.5148 | 12700 | 0.0007 | - |
|
254 |
+
| 1.5267 | 12800 | 0.0017 | - |
|
255 |
+
| 1.5386 | 12900 | 0.0005 | - |
|
256 |
+
| 1.5506 | 13000 | 0.0006 | - |
|
257 |
+
| 1.5625 | 13100 | 0.0019 | - |
|
258 |
+
| 1.5744 | 13200 | 0.0004 | - |
|
259 |
+
| 1.5864 | 13300 | 0.0007 | - |
|
260 |
+
| 1.5983 | 13400 | 0.0005 | - |
|
261 |
+
| 1.6102 | 13500 | 0.0006 | - |
|
262 |
+
| 1.6221 | 13600 | 0.0003 | - |
|
263 |
+
| 1.6341 | 13700 | 0.0004 | - |
|
264 |
+
| 1.6460 | 13800 | 0.0003 | - |
|
265 |
+
| 1.6579 | 13900 | 0.0003 | - |
|
266 |
+
| 1.6698 | 14000 | 0.0006 | - |
|
267 |
+
| 1.6818 | 14100 | 0.0006 | - |
|
268 |
+
| 1.6937 | 14200 | 0.0003 | - |
|
269 |
+
| 1.7056 | 14300 | 0.0004 | - |
|
270 |
+
| 1.7176 | 14400 | 0.0003 | - |
|
271 |
+
| 1.7295 | 14500 | 0.0003 | - |
|
272 |
+
| 1.7414 | 14600 | 0.0003 | - |
|
273 |
+
| 1.7533 | 14700 | 0.0003 | - |
|
274 |
+
| 1.7653 | 14800 | 0.0004 | - |
|
275 |
+
| 1.7772 | 14900 | 0.0003 | - |
|
276 |
+
| 1.7891 | 15000 | 0.0003 | - |
|
277 |
+
| 1.8010 | 15100 | 0.0004 | - |
|
278 |
+
| 1.8130 | 15200 | 0.0004 | - |
|
279 |
+
| 1.8249 | 15300 | 0.0002 | - |
|
280 |
+
| 1.8368 | 15400 | 0.0003 | - |
|
281 |
+
| 1.8488 | 15500 | 0.0004 | - |
|
282 |
+
| 1.8607 | 15600 | 0.0003 | - |
|
283 |
+
| 1.8726 | 15700 | 0.0005 | - |
|
284 |
+
| 1.8845 | 15800 | 0.0004 | - |
|
285 |
+
| 1.8965 | 15900 | 0.0002 | - |
|
286 |
+
| 1.9084 | 16000 | 0.0002 | - |
|
287 |
+
| 1.9203 | 16100 | 0.0003 | - |
|
288 |
+
| 1.9323 | 16200 | 0.0003 | - |
|
289 |
+
| 1.9442 | 16300 | 0.0003 | - |
|
290 |
+
| 1.9561 | 16400 | 0.0004 | - |
|
291 |
+
| 1.9680 | 16500 | 0.0003 | - |
|
292 |
+
| 1.9800 | 16600 | 0.0002 | - |
|
293 |
+
| 1.9919 | 16700 | 0.0003 | - |
|
294 |
+
|
295 |
+
### Framework Versions
|
296 |
+
- Python: 3.10.4
|
297 |
+
- SetFit: 1.1.2
|
298 |
+
- Sentence Transformers: 4.0.2
|
299 |
+
- Transformers: 4.51.1
|
300 |
+
- PyTorch: 2.6.0+cu126
|
301 |
+
- Datasets: 3.5.0
|
302 |
+
- Tokenizers: 0.21.1
|
303 |
+
|
304 |
+
## Citation
|
305 |
+
|
306 |
+
### BibTeX
|
307 |
+
```bibtex
|
308 |
+
@article{https://doi.org/10.48550/arxiv.2209.11055,
|
309 |
+
doi = {10.48550/ARXIV.2209.11055},
|
310 |
+
url = {https://arxiv.org/abs/2209.11055},
|
311 |
+
author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
|
312 |
+
keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
|
313 |
+
title = {Efficient Few-Shot Learning Without Prompts},
|
314 |
+
publisher = {arXiv},
|
315 |
+
year = {2022},
|
316 |
+
copyright = {Creative Commons Attribution 4.0 International}
|
317 |
+
}
|
318 |
+
```
|
319 |
+
|
320 |
+
<!--
|
321 |
+
## Glossary
|
322 |
+
|
323 |
+
*Clearly define terms in order to be accessible across audiences.*
|
324 |
+
-->
|
325 |
+
|
326 |
+
<!--
|
327 |
+
## Model Card Authors
|
328 |
+
|
329 |
+
*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
|
330 |
+
-->
|
331 |
+
|
332 |
+
<!--
|
333 |
+
## Model Card Contact
|
334 |
+
|
335 |
+
*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
|
336 |
+
-->
|
config.json
ADDED
@@ -0,0 +1,24 @@
|
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|
|
|
|
|
|
1 |
+
{
|
2 |
+
"activation": "gelu",
|
3 |
+
"architectures": [
|
4 |
+
"DistilBertModel"
|
5 |
+
],
|
6 |
+
"attention_dropout": 0.1,
|
7 |
+
"dim": 768,
|
8 |
+
"dropout": 0.1,
|
9 |
+
"hidden_dim": 3072,
|
10 |
+
"initializer_range": 0.02,
|
11 |
+
"max_position_embeddings": 512,
|
12 |
+
"model_type": "distilbert",
|
13 |
+
"n_heads": 12,
|
14 |
+
"n_layers": 6,
|
15 |
+
"output_past": true,
|
16 |
+
"pad_token_id": 0,
|
17 |
+
"qa_dropout": 0.1,
|
18 |
+
"seq_classif_dropout": 0.2,
|
19 |
+
"sinusoidal_pos_embds": true,
|
20 |
+
"tie_weights_": true,
|
21 |
+
"torch_dtype": "float32",
|
22 |
+
"transformers_version": "4.51.1",
|
23 |
+
"vocab_size": 31102
|
24 |
+
}
|
config_sentence_transformers.json
ADDED
@@ -0,0 +1,10 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"__version__": {
|
3 |
+
"sentence_transformers": "4.0.2",
|
4 |
+
"transformers": "4.51.1",
|
5 |
+
"pytorch": "2.6.0+cu126"
|
6 |
+
},
|
7 |
+
"prompts": {},
|
8 |
+
"default_prompt_name": null,
|
9 |
+
"similarity_fn_name": "cosine"
|
10 |
+
}
|
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 sha256:88a996c8b091c0593bd26cadb54fb7e6b9d739c24ab6e034b38cc9508d6907e4
|
3 |
+
size 267244368
|
model_head.pkl
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:fee06aadeca647c6977b378f48a2971662993c8d2f272e292e67ec2e42caf132
|
3 |
+
size 23064
|
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 +1,37 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"cls_token": {
|
3 |
+
"content": "[CLS]",
|
4 |
+
"lstrip": false,
|
5 |
+
"normalized": false,
|
6 |
+
"rstrip": false,
|
7 |
+
"single_word": false
|
8 |
+
},
|
9 |
+
"mask_token": {
|
10 |
+
"content": "[MASK]",
|
11 |
+
"lstrip": false,
|
12 |
+
"normalized": false,
|
13 |
+
"rstrip": false,
|
14 |
+
"single_word": false
|
15 |
+
},
|
16 |
+
"pad_token": {
|
17 |
+
"content": "[PAD]",
|
18 |
+
"lstrip": false,
|
19 |
+
"normalized": false,
|
20 |
+
"rstrip": false,
|
21 |
+
"single_word": false
|
22 |
+
},
|
23 |
+
"sep_token": {
|
24 |
+
"content": "[SEP]",
|
25 |
+
"lstrip": false,
|
26 |
+
"normalized": false,
|
27 |
+
"rstrip": false,
|
28 |
+
"single_word": false
|
29 |
+
},
|
30 |
+
"unk_token": {
|
31 |
+
"content": "[UNK]",
|
32 |
+
"lstrip": false,
|
33 |
+
"normalized": false,
|
34 |
+
"rstrip": false,
|
35 |
+
"single_word": false
|
36 |
+
}
|
37 |
+
}
|
tokenizer.json
ADDED
The diff for this file is too large to render.
See raw diff
|
|
tokenizer_config.json
ADDED
@@ -0,0 +1,56 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
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|
|
|
|
|
|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"added_tokens_decoder": {
|
3 |
+
"0": {
|
4 |
+
"content": "[PAD]",
|
5 |
+
"lstrip": false,
|
6 |
+
"normalized": false,
|
7 |
+
"rstrip": false,
|
8 |
+
"single_word": false,
|
9 |
+
"special": true
|
10 |
+
},
|
11 |
+
"101": {
|
12 |
+
"content": "[UNK]",
|
13 |
+
"lstrip": false,
|
14 |
+
"normalized": false,
|
15 |
+
"rstrip": false,
|
16 |
+
"single_word": false,
|
17 |
+
"special": true
|
18 |
+
},
|
19 |
+
"102": {
|
20 |
+
"content": "[CLS]",
|
21 |
+
"lstrip": false,
|
22 |
+
"normalized": false,
|
23 |
+
"rstrip": false,
|
24 |
+
"single_word": false,
|
25 |
+
"special": true
|
26 |
+
},
|
27 |
+
"103": {
|
28 |
+
"content": "[SEP]",
|
29 |
+
"lstrip": false,
|
30 |
+
"normalized": false,
|
31 |
+
"rstrip": false,
|
32 |
+
"single_word": false,
|
33 |
+
"special": true
|
34 |
+
},
|
35 |
+
"104": {
|
36 |
+
"content": "[MASK]",
|
37 |
+
"lstrip": false,
|
38 |
+
"normalized": false,
|
39 |
+
"rstrip": false,
|
40 |
+
"single_word": false,
|
41 |
+
"special": true
|
42 |
+
}
|
43 |
+
},
|
44 |
+
"clean_up_tokenization_spaces": false,
|
45 |
+
"cls_token": "[CLS]",
|
46 |
+
"do_lower_case": false,
|
47 |
+
"extra_special_tokens": {},
|
48 |
+
"mask_token": "[MASK]",
|
49 |
+
"model_max_length": 512,
|
50 |
+
"pad_token": "[PAD]",
|
51 |
+
"sep_token": "[SEP]",
|
52 |
+
"strip_accents": null,
|
53 |
+
"tokenize_chinese_chars": true,
|
54 |
+
"tokenizer_class": "DistilBertTokenizer",
|
55 |
+
"unk_token": "[UNK]"
|
56 |
+
}
|
vocab.txt
ADDED
The diff for this file is too large to render.
See raw diff
|
|