---
tags:
- setfit
- sentence-transformers
- text-classification
- generated_from_setfit_trainer
widget:
- text: Encourage interoperability of farm-management systems with national tax and
    regulatory reporting to reduce administrative burden.
- text: Support critical infrastructure investments for rural bioenergy supply chains,
    including feedstock storage, processing facilities, and logistics, to reduce post-harvest
    losses and strengthen resilience.
- text: Policy coherence will be strengthened by aligning agricultural, forestry,
    and fisheries policies with international instruments on biodiversity and sustainable
    use of ecosystems, ensuring that area restoration and sustainable fishing goals
    are mutually reinforcing. The approach will be backed by sectoral budgets and
    performance-based support to encourage early adoption.
- text: Financing windows will be created to de-risk early-stage bioenergy ventures,
    including blended finance and concessional lending.
- text: Foster regional integration to broaden market access, reduce dependence on
    a narrow product mix, and enhance resilience of the agrifood trade profile in
    the face of global price volatility.
metrics:
- accuracy
pipeline_tag: text-classification
library_name: setfit
inference: false
base_model: sentence-transformers/paraphrase-multilingual-mpnet-base-v2
---

# SetFit with sentence-transformers/paraphrase-multilingual-mpnet-base-v2

This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [sentence-transformers/paraphrase-multilingual-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-multilingual-mpnet-base-v2) as the Sentence Transformer embedding model. A OneVsRestClassifier instance is used for classification.

The model has been trained using an efficient few-shot learning technique that involves:

1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.
2. Training a classification head with features from the fine-tuned Sentence Transformer.

## Model Details

### Model Description
- **Model Type:** SetFit
- **Sentence Transformer body:** [sentence-transformers/paraphrase-multilingual-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-multilingual-mpnet-base-v2)
- **Classification head:** a OneVsRestClassifier instance
- **Maximum Sequence Length:** 128 tokens
- **Number of Classes:** 96 classes
<!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
<!-- - **Language:** Unknown -->
<!-- - **License:** Unknown -->

### Model Sources

- **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit)
- **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055)
- **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)

## Uses

### Direct Use for Inference

First install the SetFit library:

```bash
pip install setfit
```

Then you can load this model and run inference.

```python
from setfit import SetFitModel

# Download from the 🤗 Hub
model = SetFitModel.from_pretrained("faodl/model_cca_multilabel_mpnet-65max-data-augmented-v03")
# Run inference
preds = model("Financing windows will be created to de-risk early-stage bioenergy ventures, including blended finance and concessional lending.")
```

<!--
### Downstream Use

*List how someone could finetune this model on their own dataset.*
-->

<!--
### Out-of-Scope Use

*List how the model may foreseeably be misused and address what users ought not to do with the model.*
-->

<!--
## Bias, Risks and Limitations

*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
-->

<!--
### Recommendations

*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
-->

## Training Details

### Training Set Metrics
| Training set | Min | Median  | Max |
|:-------------|:----|:--------|:----|
| Word count   | 1   | 47.2721 | 947 |

### Training Hyperparameters
- batch_size: (8, 8)
- num_epochs: (2, 2)
- max_steps: -1
- sampling_strategy: oversampling
- num_iterations: 10
- body_learning_rate: (2e-05, 2e-05)
- head_learning_rate: 2e-05
- loss: CosineSimilarityLoss
- distance_metric: cosine_distance
- margin: 0.25
- end_to_end: False
- use_amp: False
- warmup_proportion: 0.1
- l2_weight: 0.01
- seed: 42
- eval_max_steps: -1
- load_best_model_at_end: False

### Training Results
| Epoch  | Step  | Training Loss | Validation Loss |
|:------:|:-----:|:-------------:|:---------------:|
| 0.0001 | 1     | 0.3187        | -               |
| 0.0032 | 50    | 0.2107        | -               |
| 0.0065 | 100   | 0.2079        | -               |
| 0.0097 | 150   | 0.2015        | -               |
| 0.0130 | 200   | 0.2011        | -               |
| 0.0162 | 250   | 0.1917        | -               |
| 0.0194 | 300   | 0.187         | -               |
| 0.0227 | 350   | 0.1892        | -               |
| 0.0259 | 400   | 0.1726        | -               |
| 0.0291 | 450   | 0.1776        | -               |
| 0.0324 | 500   | 0.1685        | -               |
| 0.0356 | 550   | 0.176         | -               |
| 0.0389 | 600   | 0.1646        | -               |
| 0.0421 | 650   | 0.1689        | -               |
| 0.0453 | 700   | 0.1577        | -               |
| 0.0486 | 750   | 0.1466        | -               |
| 0.0518 | 800   | 0.1534        | -               |
| 0.0551 | 850   | 0.1606        | -               |
| 0.0583 | 900   | 0.149         | -               |
| 0.0615 | 950   | 0.1414        | -               |
| 0.0648 | 1000  | 0.1357        | -               |
| 0.0680 | 1050  | 0.1483        | -               |
| 0.0713 | 1100  | 0.1302        | -               |
| 0.0745 | 1150  | 0.14          | -               |
| 0.0777 | 1200  | 0.1479        | -               |
| 0.0810 | 1250  | 0.1496        | -               |
| 0.0842 | 1300  | 0.1308        | -               |
| 0.0874 | 1350  | 0.1509        | -               |
| 0.0907 | 1400  | 0.15          | -               |
| 0.0939 | 1450  | 0.1516        | -               |
| 0.0972 | 1500  | 0.1319        | -               |
| 0.1004 | 1550  | 0.1349        | -               |
| 0.1036 | 1600  | 0.1398        | -               |
| 0.1069 | 1650  | 0.1276        | -               |
| 0.1101 | 1700  | 0.1309        | -               |
| 0.1134 | 1750  | 0.1408        | -               |
| 0.1166 | 1800  | 0.1416        | -               |
| 0.1198 | 1850  | 0.1371        | -               |
| 0.1231 | 1900  | 0.1266        | -               |
| 0.1263 | 1950  | 0.1257        | -               |
| 0.1296 | 2000  | 0.1337        | -               |
| 0.1328 | 2050  | 0.1475        | -               |
| 0.1360 | 2100  | 0.1412        | -               |
| 0.1393 | 2150  | 0.1412        | -               |
| 0.1425 | 2200  | 0.1281        | -               |
| 0.1457 | 2250  | 0.1293        | -               |
| 0.1490 | 2300  | 0.1186        | -               |
| 0.1522 | 2350  | 0.142         | -               |
| 0.1555 | 2400  | 0.1327        | -               |
| 0.1587 | 2450  | 0.1356        | -               |
| 0.1619 | 2500  | 0.1357        | -               |
| 0.1652 | 2550  | 0.1235        | -               |
| 0.1684 | 2600  | 0.1448        | -               |
| 0.1717 | 2650  | 0.1274        | -               |
| 0.1749 | 2700  | 0.1138        | -               |
| 0.1781 | 2750  | 0.13          | -               |
| 0.1814 | 2800  | 0.1231        | -               |
| 0.1846 | 2850  | 0.1258        | -               |
| 0.1878 | 2900  | 0.1148        | -               |
| 0.1911 | 2950  | 0.1249        | -               |
| 0.1943 | 3000  | 0.1281        | -               |
| 0.1976 | 3050  | 0.1239        | -               |
| 0.2008 | 3100  | 0.1205        | -               |
| 0.2040 | 3150  | 0.1265        | -               |
| 0.2073 | 3200  | 0.1371        | -               |
| 0.2105 | 3250  | 0.1285        | -               |
| 0.2138 | 3300  | 0.1365        | -               |
| 0.2170 | 3350  | 0.1344        | -               |
| 0.2202 | 3400  | 0.1329        | -               |
| 0.2235 | 3450  | 0.1393        | -               |
| 0.2267 | 3500  | 0.1313        | -               |
| 0.2300 | 3550  | 0.1141        | -               |
| 0.2332 | 3600  | 0.1255        | -               |
| 0.2364 | 3650  | 0.1239        | -               |
| 0.2397 | 3700  | 0.1215        | -               |
| 0.2429 | 3750  | 0.1208        | -               |
| 0.2461 | 3800  | 0.1339        | -               |
| 0.2494 | 3850  | 0.1298        | -               |
| 0.2526 | 3900  | 0.1275        | -               |
| 0.2559 | 3950  | 0.126         | -               |
| 0.2591 | 4000  | 0.1106        | -               |
| 0.2623 | 4050  | 0.1301        | -               |
| 0.2656 | 4100  | 0.1066        | -               |
| 0.2688 | 4150  | 0.1309        | -               |
| 0.2721 | 4200  | 0.1205        | -               |
| 0.2753 | 4250  | 0.1371        | -               |
| 0.2785 | 4300  | 0.1215        | -               |
| 0.2818 | 4350  | 0.1204        | -               |
| 0.2850 | 4400  | 0.1183        | -               |
| 0.2882 | 4450  | 0.1189        | -               |
| 0.2915 | 4500  | 0.1129        | -               |
| 0.2947 | 4550  | 0.115         | -               |
| 0.2980 | 4600  | 0.1152        | -               |
| 0.3012 | 4650  | 0.1122        | -               |
| 0.3044 | 4700  | 0.1217        | -               |
| 0.3077 | 4750  | 0.103         | -               |
| 0.3109 | 4800  | 0.1203        | -               |
| 0.3142 | 4850  | 0.1253        | -               |
| 0.3174 | 4900  | 0.1123        | -               |
| 0.3206 | 4950  | 0.1262        | -               |
| 0.3239 | 5000  | 0.1115        | -               |
| 0.3271 | 5050  | 0.1219        | -               |
| 0.3304 | 5100  | 0.1185        | -               |
| 0.3336 | 5150  | 0.1242        | -               |
| 0.3368 | 5200  | 0.123         | -               |
| 0.3401 | 5250  | 0.1055        | -               |
| 0.3433 | 5300  | 0.116         | -               |
| 0.3465 | 5350  | 0.1173        | -               |
| 0.3498 | 5400  | 0.1116        | -               |
| 0.3530 | 5450  | 0.1173        | -               |
| 0.3563 | 5500  | 0.107         | -               |
| 0.3595 | 5550  | 0.1052        | -               |
| 0.3627 | 5600  | 0.1119        | -               |
| 0.3660 | 5650  | 0.1116        | -               |
| 0.3692 | 5700  | 0.1153        | -               |
| 0.3725 | 5750  | 0.1039        | -               |
| 0.3757 | 5800  | 0.1187        | -               |
| 0.3789 | 5850  | 0.1106        | -               |
| 0.3822 | 5900  | 0.111         | -               |
| 0.3854 | 5950  | 0.1018        | -               |
| 0.3887 | 6000  | 0.1065        | -               |
| 0.3919 | 6050  | 0.1044        | -               |
| 0.3951 | 6100  | 0.1037        | -               |
| 0.3984 | 6150  | 0.0991        | -               |
| 0.4016 | 6200  | 0.0984        | -               |
| 0.4048 | 6250  | 0.1058        | -               |
| 0.4081 | 6300  | 0.0954        | -               |
| 0.4113 | 6350  | 0.0883        | -               |
| 0.4146 | 6400  | 0.1077        | -               |
| 0.4178 | 6450  | 0.1134        | -               |
| 0.4210 | 6500  | 0.1079        | -               |
| 0.4243 | 6550  | 0.0996        | -               |
| 0.4275 | 6600  | 0.1045        | -               |
| 0.4308 | 6650  | 0.1151        | -               |
| 0.4340 | 6700  | 0.1062        | -               |
| 0.4372 | 6750  | 0.1077        | -               |
| 0.4405 | 6800  | 0.1133        | -               |
| 0.4437 | 6850  | 0.1096        | -               |
| 0.4469 | 6900  | 0.1017        | -               |
| 0.4502 | 6950  | 0.0972        | -               |
| 0.4534 | 7000  | 0.0955        | -               |
| 0.4567 | 7050  | 0.0986        | -               |
| 0.4599 | 7100  | 0.0942        | -               |
| 0.4631 | 7150  | 0.1093        | -               |
| 0.4664 | 7200  | 0.0908        | -               |
| 0.4696 | 7250  | 0.1165        | -               |
| 0.4729 | 7300  | 0.0979        | -               |
| 0.4761 | 7350  | 0.0915        | -               |
| 0.4793 | 7400  | 0.0824        | -               |
| 0.4826 | 7450  | 0.0988        | -               |
| 0.4858 | 7500  | 0.112         | -               |
| 0.4891 | 7550  | 0.0997        | -               |
| 0.4923 | 7600  | 0.1013        | -               |
| 0.4955 | 7650  | 0.1119        | -               |
| 0.4988 | 7700  | 0.1087        | -               |
| 0.5020 | 7750  | 0.1037        | -               |
| 0.5052 | 7800  | 0.0995        | -               |
| 0.5085 | 7850  | 0.0913        | -               |
| 0.5117 | 7900  | 0.1006        | -               |
| 0.5150 | 7950  | 0.0916        | -               |
| 0.5182 | 8000  | 0.0861        | -               |
| 0.5214 | 8050  | 0.1135        | -               |
| 0.5247 | 8100  | 0.0956        | -               |
| 0.5279 | 8150  | 0.1007        | -               |
| 0.5312 | 8200  | 0.0898        | -               |
| 0.5344 | 8250  | 0.1079        | -               |
| 0.5376 | 8300  | 0.093         | -               |
| 0.5409 | 8350  | 0.0957        | -               |
| 0.5441 | 8400  | 0.0945        | -               |
| 0.5474 | 8450  | 0.0929        | -               |
| 0.5506 | 8500  | 0.0933        | -               |
| 0.5538 | 8550  | 0.0948        | -               |
| 0.5571 | 8600  | 0.0793        | -               |
| 0.5603 | 8650  | 0.0888        | -               |
| 0.5635 | 8700  | 0.0835        | -               |
| 0.5668 | 8750  | 0.0809        | -               |
| 0.5700 | 8800  | 0.1069        | -               |
| 0.5733 | 8850  | 0.0885        | -               |
| 0.5765 | 8900  | 0.089         | -               |
| 0.5797 | 8950  | 0.1028        | -               |
| 0.5830 | 9000  | 0.0842        | -               |
| 0.5862 | 9050  | 0.0946        | -               |
| 0.5895 | 9100  | 0.0989        | -               |
| 0.5927 | 9150  | 0.0827        | -               |
| 0.5959 | 9200  | 0.0798        | -               |
| 0.5992 | 9250  | 0.0855        | -               |
| 0.6024 | 9300  | 0.091         | -               |
| 0.6056 | 9350  | 0.0905        | -               |
| 0.6089 | 9400  | 0.0844        | -               |
| 0.6121 | 9450  | 0.0783        | -               |
| 0.6154 | 9500  | 0.0838        | -               |
| 0.6186 | 9550  | 0.0992        | -               |
| 0.6218 | 9600  | 0.0954        | -               |
| 0.6251 | 9650  | 0.0817        | -               |
| 0.6283 | 9700  | 0.0895        | -               |
| 0.6316 | 9750  | 0.0818        | -               |
| 0.6348 | 9800  | 0.0806        | -               |
| 0.6380 | 9850  | 0.0895        | -               |
| 0.6413 | 9900  | 0.0925        | -               |
| 0.6445 | 9950  | 0.0865        | -               |
| 0.6478 | 10000 | 0.0881        | -               |
| 0.6510 | 10050 | 0.0804        | -               |
| 0.6542 | 10100 | 0.0951        | -               |
| 0.6575 | 10150 | 0.0998        | -               |
| 0.6607 | 10200 | 0.0892        | -               |
| 0.6639 | 10250 | 0.0824        | -               |
| 0.6672 | 10300 | 0.0856        | -               |
| 0.6704 | 10350 | 0.0821        | -               |
| 0.6737 | 10400 | 0.0949        | -               |
| 0.6769 | 10450 | 0.0918        | -               |
| 0.6801 | 10500 | 0.0868        | -               |
| 0.6834 | 10550 | 0.0922        | -               |
| 0.6866 | 10600 | 0.0845        | -               |
| 0.6899 | 10650 | 0.0752        | -               |
| 0.6931 | 10700 | 0.0904        | -               |
| 0.6963 | 10750 | 0.0837        | -               |
| 0.6996 | 10800 | 0.0846        | -               |
| 0.7028 | 10850 | 0.0904        | -               |
| 0.7061 | 10900 | 0.0819        | -               |
| 0.7093 | 10950 | 0.0851        | -               |
| 0.7125 | 11000 | 0.0755        | -               |
| 0.7158 | 11050 | 0.0856        | -               |
| 0.7190 | 11100 | 0.0978        | -               |
| 0.7222 | 11150 | 0.0764        | -               |
| 0.7255 | 11200 | 0.0837        | -               |
| 0.7287 | 11250 | 0.0896        | -               |
| 0.7320 | 11300 | 0.0878        | -               |
| 0.7352 | 11350 | 0.0799        | -               |
| 0.7384 | 11400 | 0.0819        | -               |
| 0.7417 | 11450 | 0.0864        | -               |
| 0.7449 | 11500 | 0.085         | -               |
| 0.7482 | 11550 | 0.092         | -               |
| 0.7514 | 11600 | 0.08          | -               |
| 0.7546 | 11650 | 0.0828        | -               |
| 0.7579 | 11700 | 0.078         | -               |
| 0.7611 | 11750 | 0.0787        | -               |
| 0.7643 | 11800 | 0.0818        | -               |
| 0.7676 | 11850 | 0.0872        | -               |
| 0.7708 | 11900 | 0.0857        | -               |
| 0.7741 | 11950 | 0.0891        | -               |
| 0.7773 | 12000 | 0.0731        | -               |
| 0.7805 | 12050 | 0.0881        | -               |
| 0.7838 | 12100 | 0.0735        | -               |
| 0.7870 | 12150 | 0.0825        | -               |
| 0.7903 | 12200 | 0.0799        | -               |
| 0.7935 | 12250 | 0.0783        | -               |
| 0.7967 | 12300 | 0.081         | -               |
| 0.8000 | 12350 | 0.0847        | -               |
| 0.8032 | 12400 | 0.0851        | -               |
| 0.8065 | 12450 | 0.0783        | -               |
| 0.8097 | 12500 | 0.0634        | -               |
| 0.8129 | 12550 | 0.0767        | -               |
| 0.8162 | 12600 | 0.0836        | -               |
| 0.8194 | 12650 | 0.0871        | -               |
| 0.8226 | 12700 | 0.0787        | -               |
| 0.8259 | 12750 | 0.0755        | -               |
| 0.8291 | 12800 | 0.0787        | -               |
| 0.8324 | 12850 | 0.0764        | -               |
| 0.8356 | 12900 | 0.077         | -               |
| 0.8388 | 12950 | 0.0821        | -               |
| 0.8421 | 13000 | 0.0756        | -               |
| 0.8453 | 13050 | 0.0798        | -               |
| 0.8486 | 13100 | 0.0699        | -               |
| 0.8518 | 13150 | 0.0823        | -               |
| 0.8550 | 13200 | 0.0783        | -               |
| 0.8583 | 13250 | 0.078         | -               |
| 0.8615 | 13300 | 0.0742        | -               |
| 0.8647 | 13350 | 0.078         | -               |
| 0.8680 | 13400 | 0.0835        | -               |
| 0.8712 | 13450 | 0.0719        | -               |
| 0.8745 | 13500 | 0.0774        | -               |
| 0.8777 | 13550 | 0.0855        | -               |
| 0.8809 | 13600 | 0.0873        | -               |
| 0.8842 | 13650 | 0.084         | -               |
| 0.8874 | 13700 | 0.0853        | -               |
| 0.8907 | 13750 | 0.0833        | -               |
| 0.8939 | 13800 | 0.0811        | -               |
| 0.8971 | 13850 | 0.0727        | -               |
| 0.9004 | 13900 | 0.0677        | -               |
| 0.9036 | 13950 | 0.0666        | -               |
| 0.9069 | 14000 | 0.0764        | -               |
| 0.9101 | 14050 | 0.0729        | -               |
| 0.9133 | 14100 | 0.0781        | -               |
| 0.9166 | 14150 | 0.0917        | -               |
| 0.9198 | 14200 | 0.0878        | -               |
| 0.9230 | 14250 | 0.0734        | -               |
| 0.9263 | 14300 | 0.0825        | -               |
| 0.9295 | 14350 | 0.0799        | -               |
| 0.9328 | 14400 | 0.0817        | -               |
| 0.9360 | 14450 | 0.0757        | -               |
| 0.9392 | 14500 | 0.0755        | -               |
| 0.9425 | 14550 | 0.062         | -               |
| 0.9457 | 14600 | 0.0829        | -               |
| 0.9490 | 14650 | 0.0718        | -               |
| 0.9522 | 14700 | 0.0776        | -               |
| 0.9554 | 14750 | 0.0744        | -               |
| 0.9587 | 14800 | 0.0881        | -               |
| 0.9619 | 14850 | 0.0813        | -               |
| 0.9652 | 14900 | 0.0673        | -               |
| 0.9684 | 14950 | 0.0819        | -               |
| 0.9716 | 15000 | 0.0566        | -               |
| 0.9749 | 15050 | 0.0849        | -               |
| 0.9781 | 15100 | 0.0736        | -               |
| 0.9813 | 15150 | 0.0661        | -               |
| 0.9846 | 15200 | 0.0731        | -               |
| 0.9878 | 15250 | 0.0779        | -               |
| 0.9911 | 15300 | 0.0723        | -               |
| 0.9943 | 15350 | 0.0606        | -               |
| 0.9975 | 15400 | 0.0801        | -               |
| 1.0008 | 15450 | 0.0675        | -               |
| 1.0040 | 15500 | 0.0743        | -               |
| 1.0073 | 15550 | 0.0655        | -               |
| 1.0105 | 15600 | 0.0594        | -               |
| 1.0137 | 15650 | 0.0642        | -               |
| 1.0170 | 15700 | 0.059         | -               |
| 1.0202 | 15750 | 0.0628        | -               |
| 1.0234 | 15800 | 0.0569        | -               |
| 1.0267 | 15850 | 0.0725        | -               |
| 1.0299 | 15900 | 0.0744        | -               |
| 1.0332 | 15950 | 0.056         | -               |
| 1.0364 | 16000 | 0.0754        | -               |
| 1.0396 | 16050 | 0.0694        | -               |
| 1.0429 | 16100 | 0.057         | -               |
| 1.0461 | 16150 | 0.0706        | -               |
| 1.0494 | 16200 | 0.0675        | -               |
| 1.0526 | 16250 | 0.0679        | -               |
| 1.0558 | 16300 | 0.0745        | -               |
| 1.0591 | 16350 | 0.0539        | -               |
| 1.0623 | 16400 | 0.0708        | -               |
| 1.0656 | 16450 | 0.0629        | -               |
| 1.0688 | 16500 | 0.0699        | -               |
| 1.0720 | 16550 | 0.0706        | -               |
| 1.0753 | 16600 | 0.0717        | -               |
| 1.0785 | 16650 | 0.0676        | -               |
| 1.0817 | 16700 | 0.0619        | -               |
| 1.0850 | 16750 | 0.07          | -               |
| 1.0882 | 16800 | 0.0569        | -               |
| 1.0915 | 16850 | 0.0615        | -               |
| 1.0947 | 16900 | 0.0646        | -               |
| 1.0979 | 16950 | 0.0651        | -               |
| 1.1012 | 17000 | 0.072         | -               |
| 1.1044 | 17050 | 0.0693        | -               |
| 1.1077 | 17100 | 0.0681        | -               |
| 1.1109 | 17150 | 0.0509        | -               |
| 1.1141 | 17200 | 0.0604        | -               |
| 1.1174 | 17250 | 0.0723        | -               |
| 1.1206 | 17300 | 0.0726        | -               |
| 1.1239 | 17350 | 0.062         | -               |
| 1.1271 | 17400 | 0.0608        | -               |
| 1.1303 | 17450 | 0.0649        | -               |
| 1.1336 | 17500 | 0.0631        | -               |
| 1.1368 | 17550 | 0.0623        | -               |
| 1.1400 | 17600 | 0.0707        | -               |
| 1.1433 | 17650 | 0.0708        | -               |
| 1.1465 | 17700 | 0.0736        | -               |
| 1.1498 | 17750 | 0.0674        | -               |
| 1.1530 | 17800 | 0.0759        | -               |
| 1.1562 | 17850 | 0.0614        | -               |
| 1.1595 | 17900 | 0.0626        | -               |
| 1.1627 | 17950 | 0.0741        | -               |
| 1.1660 | 18000 | 0.065         | -               |
| 1.1692 | 18050 | 0.069         | -               |
| 1.1724 | 18100 | 0.0749        | -               |
| 1.1757 | 18150 | 0.0554        | -               |
| 1.1789 | 18200 | 0.068         | -               |
| 1.1821 | 18250 | 0.0676        | -               |
| 1.1854 | 18300 | 0.067         | -               |
| 1.1886 | 18350 | 0.0682        | -               |
| 1.1919 | 18400 | 0.0546        | -               |
| 1.1951 | 18450 | 0.068         | -               |
| 1.1983 | 18500 | 0.0633        | -               |
| 1.2016 | 18550 | 0.0627        | -               |
| 1.2048 | 18600 | 0.0608        | -               |
| 1.2081 | 18650 | 0.0625        | -               |
| 1.2113 | 18700 | 0.0652        | -               |
| 1.2145 | 18750 | 0.0555        | -               |
| 1.2178 | 18800 | 0.0615        | -               |
| 1.2210 | 18850 | 0.0599        | -               |
| 1.2243 | 18900 | 0.0664        | -               |
| 1.2275 | 18950 | 0.0653        | -               |
| 1.2307 | 19000 | 0.0481        | -               |
| 1.2340 | 19050 | 0.055         | -               |
| 1.2372 | 19100 | 0.0681        | -               |
| 1.2404 | 19150 | 0.0589        | -               |
| 1.2437 | 19200 | 0.0774        | -               |
| 1.2469 | 19250 | 0.0624        | -               |
| 1.2502 | 19300 | 0.0609        | -               |
| 1.2534 | 19350 | 0.0545        | -               |
| 1.2566 | 19400 | 0.0546        | -               |
| 1.2599 | 19450 | 0.087         | -               |
| 1.2631 | 19500 | 0.061         | -               |
| 1.2664 | 19550 | 0.068         | -               |
| 1.2696 | 19600 | 0.0708        | -               |
| 1.2728 | 19650 | 0.0651        | -               |
| 1.2761 | 19700 | 0.0713        | -               |
| 1.2793 | 19750 | 0.0646        | -               |
| 1.2825 | 19800 | 0.0559        | -               |
| 1.2858 | 19850 | 0.0486        | -               |
| 1.2890 | 19900 | 0.0583        | -               |
| 1.2923 | 19950 | 0.0549        | -               |
| 1.2955 | 20000 | 0.073         | -               |
| 1.2987 | 20050 | 0.0633        | -               |
| 1.3020 | 20100 | 0.072         | -               |
| 1.3052 | 20150 | 0.0623        | -               |
| 1.3085 | 20200 | 0.0725        | -               |
| 1.3117 | 20250 | 0.0629        | -               |
| 1.3149 | 20300 | 0.0614        | -               |
| 1.3182 | 20350 | 0.0607        | -               |
| 1.3214 | 20400 | 0.0624        | -               |
| 1.3247 | 20450 | 0.0627        | -               |
| 1.3279 | 20500 | 0.0602        | -               |
| 1.3311 | 20550 | 0.062         | -               |
| 1.3344 | 20600 | 0.066         | -               |
| 1.3376 | 20650 | 0.0596        | -               |
| 1.3408 | 20700 | 0.0517        | -               |
| 1.3441 | 20750 | 0.057         | -               |
| 1.3473 | 20800 | 0.0584        | -               |
| 1.3506 | 20850 | 0.0576        | -               |
| 1.3538 | 20900 | 0.0667        | -               |
| 1.3570 | 20950 | 0.0672        | -               |
| 1.3603 | 21000 | 0.0641        | -               |
| 1.3635 | 21050 | 0.0545        | -               |
| 1.3668 | 21100 | 0.0609        | -               |
| 1.3700 | 21150 | 0.0639        | -               |
| 1.3732 | 21200 | 0.0612        | -               |
| 1.3765 | 21250 | 0.0623        | -               |
| 1.3797 | 21300 | 0.0645        | -               |
| 1.3830 | 21350 | 0.0676        | -               |
| 1.3862 | 21400 | 0.0704        | -               |
| 1.3894 | 21450 | 0.0569        | -               |
| 1.3927 | 21500 | 0.066         | -               |
| 1.3959 | 21550 | 0.0632        | -               |
| 1.3991 | 21600 | 0.0682        | -               |
| 1.4024 | 21650 | 0.0694        | -               |
| 1.4056 | 21700 | 0.0713        | -               |
| 1.4089 | 21750 | 0.0508        | -               |
| 1.4121 | 21800 | 0.0613        | -               |
| 1.4153 | 21850 | 0.0512        | -               |
| 1.4186 | 21900 | 0.0481        | -               |
| 1.4218 | 21950 | 0.0578        | -               |
| 1.4251 | 22000 | 0.0553        | -               |
| 1.4283 | 22050 | 0.0599        | -               |
| 1.4315 | 22100 | 0.0626        | -               |
| 1.4348 | 22150 | 0.0577        | -               |
| 1.4380 | 22200 | 0.0611        | -               |
| 1.4412 | 22250 | 0.0579        | -               |
| 1.4445 | 22300 | 0.0678        | -               |
| 1.4477 | 22350 | 0.0627        | -               |
| 1.4510 | 22400 | 0.0582        | -               |
| 1.4542 | 22450 | 0.0613        | -               |
| 1.4574 | 22500 | 0.0584        | -               |
| 1.4607 | 22550 | 0.0586        | -               |
| 1.4639 | 22600 | 0.0589        | -               |
| 1.4672 | 22650 | 0.0535        | -               |
| 1.4704 | 22700 | 0.0526        | -               |
| 1.4736 | 22750 | 0.0599        | -               |
| 1.4769 | 22800 | 0.0549        | -               |
| 1.4801 | 22850 | 0.0598        | -               |
| 1.4834 | 22900 | 0.0584        | -               |
| 1.4866 | 22950 | 0.0657        | -               |
| 1.4898 | 23000 | 0.056         | -               |
| 1.4931 | 23050 | 0.061         | -               |
| 1.4963 | 23100 | 0.0567        | -               |
| 1.4995 | 23150 | 0.0604        | -               |
| 1.5028 | 23200 | 0.053         | -               |
| 1.5060 | 23250 | 0.0577        | -               |
| 1.5093 | 23300 | 0.0552        | -               |
| 1.5125 | 23350 | 0.0675        | -               |
| 1.5157 | 23400 | 0.0698        | -               |
| 1.5190 | 23450 | 0.0577        | -               |
| 1.5222 | 23500 | 0.0518        | -               |
| 1.5255 | 23550 | 0.0552        | -               |
| 1.5287 | 23600 | 0.0606        | -               |
| 1.5319 | 23650 | 0.0598        | -               |
| 1.5352 | 23700 | 0.0586        | -               |
| 1.5384 | 23750 | 0.0562        | -               |
| 1.5417 | 23800 | 0.0571        | -               |
| 1.5449 | 23850 | 0.0525        | -               |
| 1.5481 | 23900 | 0.0619        | -               |
| 1.5514 | 23950 | 0.0558        | -               |
| 1.5546 | 24000 | 0.0651        | -               |
| 1.5578 | 24050 | 0.0595        | -               |
| 1.5611 | 24100 | 0.0669        | -               |
| 1.5643 | 24150 | 0.0576        | -               |
| 1.5676 | 24200 | 0.0498        | -               |
| 1.5708 | 24250 | 0.0613        | -               |
| 1.5740 | 24300 | 0.0544        | -               |
| 1.5773 | 24350 | 0.0566        | -               |
| 1.5805 | 24400 | 0.0613        | -               |
| 1.5838 | 24450 | 0.0597        | -               |
| 1.5870 | 24500 | 0.0525        | -               |
| 1.5902 | 24550 | 0.0537        | -               |
| 1.5935 | 24600 | 0.0613        | -               |
| 1.5967 | 24650 | 0.0446        | -               |
| 1.5999 | 24700 | 0.0597        | -               |
| 1.6032 | 24750 | 0.0601        | -               |
| 1.6064 | 24800 | 0.0521        | -               |
| 1.6097 | 24850 | 0.0584        | -               |
| 1.6129 | 24900 | 0.0591        | -               |
| 1.6161 | 24950 | 0.0593        | -               |
| 1.6194 | 25000 | 0.0562        | -               |
| 1.6226 | 25050 | 0.0586        | -               |
| 1.6259 | 25100 | 0.0593        | -               |
| 1.6291 | 25150 | 0.0615        | -               |
| 1.6323 | 25200 | 0.0492        | -               |
| 1.6356 | 25250 | 0.0573        | -               |
| 1.6388 | 25300 | 0.0631        | -               |
| 1.6421 | 25350 | 0.0444        | -               |
| 1.6453 | 25400 | 0.0587        | -               |
| 1.6485 | 25450 | 0.0601        | -               |
| 1.6518 | 25500 | 0.0565        | -               |
| 1.6550 | 25550 | 0.0654        | -               |
| 1.6582 | 25600 | 0.0558        | -               |
| 1.6615 | 25650 | 0.0537        | -               |
| 1.6647 | 25700 | 0.0504        | -               |
| 1.6680 | 25750 | 0.0549        | -               |
| 1.6712 | 25800 | 0.0517        | -               |
| 1.6744 | 25850 | 0.0621        | -               |
| 1.6777 | 25900 | 0.0468        | -               |
| 1.6809 | 25950 | 0.059         | -               |
| 1.6842 | 26000 | 0.0607        | -               |
| 1.6874 | 26050 | 0.0616        | -               |
| 1.6906 | 26100 | 0.0536        | -               |
| 1.6939 | 26150 | 0.0619        | -               |
| 1.6971 | 26200 | 0.0615        | -               |
| 1.7003 | 26250 | 0.0497        | -               |
| 1.7036 | 26300 | 0.0595        | -               |
| 1.7068 | 26350 | 0.0563        | -               |
| 1.7101 | 26400 | 0.0572        | -               |
| 1.7133 | 26450 | 0.0525        | -               |
| 1.7165 | 26500 | 0.0592        | -               |
| 1.7198 | 26550 | 0.0645        | -               |
| 1.7230 | 26600 | 0.0586        | -               |
| 1.7263 | 26650 | 0.0511        | -               |
| 1.7295 | 26700 | 0.0508        | -               |
| 1.7327 | 26750 | 0.0572        | -               |
| 1.7360 | 26800 | 0.0466        | -               |
| 1.7392 | 26850 | 0.0532        | -               |
| 1.7425 | 26900 | 0.0546        | -               |
| 1.7457 | 26950 | 0.0594        | -               |
| 1.7489 | 27000 | 0.0544        | -               |
| 1.7522 | 27050 | 0.0543        | -               |
| 1.7554 | 27100 | 0.0588        | -               |
| 1.7586 | 27150 | 0.0552        | -               |
| 1.7619 | 27200 | 0.0529        | -               |
| 1.7651 | 27250 | 0.0558        | -               |
| 1.7684 | 27300 | 0.0491        | -               |
| 1.7716 | 27350 | 0.0669        | -               |
| 1.7748 | 27400 | 0.056         | -               |
| 1.7781 | 27450 | 0.0553        | -               |
| 1.7813 | 27500 | 0.0565        | -               |
| 1.7846 | 27550 | 0.063         | -               |
| 1.7878 | 27600 | 0.0548        | -               |
| 1.7910 | 27650 | 0.0541        | -               |
| 1.7943 | 27700 | 0.0469        | -               |
| 1.7975 | 27750 | 0.0493        | -               |
| 1.8008 | 27800 | 0.0644        | -               |
| 1.8040 | 27850 | 0.0557        | -               |
| 1.8072 | 27900 | 0.0582        | -               |
| 1.8105 | 27950 | 0.0517        | -               |
| 1.8137 | 28000 | 0.0564        | -               |
| 1.8169 | 28050 | 0.0591        | -               |
| 1.8202 | 28100 | 0.0545        | -               |
| 1.8234 | 28150 | 0.0486        | -               |
| 1.8267 | 28200 | 0.0568        | -               |
| 1.8299 | 28250 | 0.0461        | -               |
| 1.8331 | 28300 | 0.0622        | -               |
| 1.8364 | 28350 | 0.0499        | -               |
| 1.8396 | 28400 | 0.0634        | -               |
| 1.8429 | 28450 | 0.0584        | -               |
| 1.8461 | 28500 | 0.0648        | -               |
| 1.8493 | 28550 | 0.0628        | -               |
| 1.8526 | 28600 | 0.057         | -               |
| 1.8558 | 28650 | 0.0528        | -               |
| 1.8590 | 28700 | 0.0521        | -               |
| 1.8623 | 28750 | 0.0527        | -               |
| 1.8655 | 28800 | 0.0457        | -               |
| 1.8688 | 28850 | 0.0505        | -               |
| 1.8720 | 28900 | 0.0508        | -               |
| 1.8752 | 28950 | 0.0595        | -               |
| 1.8785 | 29000 | 0.0558        | -               |
| 1.8817 | 29050 | 0.0521        | -               |
| 1.8850 | 29100 | 0.0475        | -               |
| 1.8882 | 29150 | 0.054         | -               |
| 1.8914 | 29200 | 0.0497        | -               |
| 1.8947 | 29250 | 0.0637        | -               |
| 1.8979 | 29300 | 0.0484        | -               |
| 1.9012 | 29350 | 0.0649        | -               |
| 1.9044 | 29400 | 0.0643        | -               |
| 1.9076 | 29450 | 0.0484        | -               |
| 1.9109 | 29500 | 0.0531        | -               |
| 1.9141 | 29550 | 0.0527        | -               |
| 1.9173 | 29600 | 0.0617        | -               |
| 1.9206 | 29650 | 0.0469        | -               |
| 1.9238 | 29700 | 0.0615        | -               |
| 1.9271 | 29750 | 0.055         | -               |
| 1.9303 | 29800 | 0.055         | -               |
| 1.9335 | 29850 | 0.0658        | -               |
| 1.9368 | 29900 | 0.0483        | -               |
| 1.9400 | 29950 | 0.0559        | -               |
| 1.9433 | 30000 | 0.0481        | -               |
| 1.9465 | 30050 | 0.0719        | -               |
| 1.9497 | 30100 | 0.0589        | -               |
| 1.9530 | 30150 | 0.0498        | -               |
| 1.9562 | 30200 | 0.049         | -               |
| 1.9595 | 30250 | 0.0456        | -               |
| 1.9627 | 30300 | 0.0551        | -               |
| 1.9659 | 30350 | 0.0415        | -               |
| 1.9692 | 30400 | 0.0607        | -               |
| 1.9724 | 30450 | 0.0521        | -               |
| 1.9756 | 30500 | 0.0545        | -               |
| 1.9789 | 30550 | 0.0544        | -               |
| 1.9821 | 30600 | 0.0535        | -               |
| 1.9854 | 30650 | 0.0637        | -               |
| 1.9886 | 30700 | 0.0555        | -               |
| 1.9918 | 30750 | 0.0472        | -               |
| 1.9951 | 30800 | 0.0544        | -               |
| 1.9983 | 30850 | 0.0592        | -               |

### Framework Versions
- Python: 3.12.12
- SetFit: 1.1.3
- Sentence Transformers: 5.1.2
- Transformers: 4.57.1
- PyTorch: 2.8.0+cu126
- Datasets: 4.0.0
- Tokenizers: 0.22.1

## Citation

### BibTeX
```bibtex
@article{https://doi.org/10.48550/arxiv.2209.11055,
    doi = {10.48550/ARXIV.2209.11055},
    url = {https://arxiv.org/abs/2209.11055},
    author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
    keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
    title = {Efficient Few-Shot Learning Without Prompts},
    publisher = {arXiv},
    year = {2022},
    copyright = {Creative Commons Attribution 4.0 International}
}
```

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