setfit safetensors bert sentence-transformers text-classification generated_from_setfit_trainer arxiv:2209.11055 base_model:BAAI/bge-base-en-v1.5 base_model:finetune:BAAI/bge-base-en-v1.5 model-index region:us
---
base_model: BAAI/bge-base-en-v1.5
library_name: setfit
metrics:
- f1
- accuracy
pipeline_tag: text-classification
tags:
- setfit
- sentence-transformers
- text-classification
- generated_from_setfit_trainer
widget:
- text: Discussion on recent report publication
- text: Growth
- text: The roundtable was arranged in order to provide an overview of the work of
    Alliance members and promote international development policy positions to the
    Scottish Conservatives. During the meeting we presented the work of SCIAF and
    its campaign for a world leading climate change response. In particular SCIAF
    explained how climate change is already affecting some of the poorest communities
    in the world and is therefore a central concern for international development.
    We argued that Scotland needs to do what it can to mitigate climate change.
- text: To introduce Energy UK discuss the energy industries contribution to tackling
    climate change and discuss stage 1 of theClimate Change (Emissions Reduction Targets)
    (Scotland) Bill. Also discussed the Scottish Government's ambition on electric
    vehicles and the role of the energy industry in a successful roll out.
- text: To discuss our key asks on the Climate Change (Emissions Reduction Targets)
    (Scotland) Bill in advance of Stage 2 including support for amendments on regional
    land use partnerships and land use strategy as means to deliver climate mitigation
    for land.
inference: true
model-index:
- name: SetFit with BAAI/bge-base-en-v1.5
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: Unknown
      type: unknown
      split: test
    metrics:
    - type: f1
      value: 0.9667149059334297
      name: F1
    - type: accuracy
      value: 0.9420654911838791
      name: Accuracy
---

# SetFit with BAAI/bge-base-en-v1.5

This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) as the Sentence Transformer embedding model. A [SetFitHead](huggingface.co/docs/setfit/reference/main#setfit.SetFitHead) 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.

undefined = Health
1 = Housing
2 = Defence
3 = Climate

## Model Details

### Model Description
- **Model Type:** SetFit
- **Sentence Transformer body:** [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5)
- **Classification head:** a [SetFitHead](huggingface.co/docs/setfit/reference/main#setfit.SetFitHead) instance
- **Maximum Sequence Length:** 512 tokens
<!-- - **Number of Classes:** Unknown -->
<!-- - **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)

## Evaluation

### Metrics
| Label   | F1     | Accuracy |
|:--------|:-------|:---------|
| **all** | 0.9667 | 0.9421   |

## 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("twright8/setfit_lobbying_classifier")
# Run inference
preds = model("Growth")
```

<!--
### 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   | 39.4538 | 282 |

### Training Hyperparameters
- batch_size: (16, 2)
- num_epochs: (4, 9)
- max_steps: -1
- sampling_strategy: undersampling
- body_learning_rate: (1.0797496673911536e-05, 3.457046714445997e-05)
- head_learning_rate: 0.0004470582121407239
- loss: CoSENTLoss
- distance_metric: cosine_distance
- margin: 0.25
- end_to_end: True
- use_amp: False
- warmup_proportion: 0.1
- seed: 42
- eval_max_steps: -1
- load_best_model_at_end: True

### Training Results
| Epoch   | Step     | Training Loss | Validation Loss |
|:-------:|:--------:|:-------------:|:---------------:|
| 0.0002  | 1        | 2.097         | -               |
| 0.0077  | 50       | 8.5514        | -               |
| 0.0155  | 100      | 3.5635        | -               |
| 0.0232  | 150      | 2.9266        | -               |
| 0.0310  | 200      | 2.1173        | -               |
| 0.0387  | 250      | 3.1002        | -               |
| 0.0465  | 300      | 3.6942        | -               |
| 0.0542  | 350      | 3.4905        | -               |
| 0.0620  | 400      | 4.0804        | -               |
| 0.0697  | 450      | 1.6071        | -               |
| 0.0774  | 500      | 2.3018        | -               |
| 0.0852  | 550      | 2.3876        | -               |
| 0.0929  | 600      | 0.2511        | -               |
| 0.1007  | 650      | 0.2435        | -               |
| 0.1084  | 700      | 2.2596        | -               |
| 0.1162  | 750      | 1.121         | -               |
| 0.1239  | 800      | 0.0907        | -               |
| 0.1317  | 850      | 0.2172        | -               |
| 0.1394  | 900      | 3.06          | -               |
| 0.1471  | 950      | 0.0074        | -               |
| 0.1549  | 1000     | 0.457         | -               |
| 0.1626  | 1050     | 0.0575        | -               |
| 0.1704  | 1100     | 0.0002        | -               |
| 0.1781  | 1150     | 0.0003        | -               |
| 0.1859  | 1200     | 0.0047        | -               |
| 0.1936  | 1250     | 0.0004        | -               |
| 0.2014  | 1300     | 0.0006        | -               |
| 0.2091  | 1350     | 0.0027        | -               |
| 0.2169  | 1400     | 0.0004        | -               |
| 0.2246  | 1450     | 0.0009        | -               |
| 0.2323  | 1500     | 0.0006        | -               |
| 0.2401  | 1550     | 0.0003        | -               |
| 0.2478  | 1600     | 0.0077        | -               |
| 0.2556  | 1650     | 0.0004        | -               |
| 0.2633  | 1700     | 0.0003        | -               |
| 0.2711  | 1750     | 0.0005        | -               |
| 0.2788  | 1800     | 0.0004        | -               |
| 0.2866  | 1850     | 0.0007        | -               |
| 0.2943  | 1900     | 0.0009        | -               |
| 0.3020  | 1950     | 0.0062        | -               |
| 0.3098  | 2000     | 0.0003        | -               |
| 0.3175  | 2050     | 0.0001        | -               |
| 0.3253  | 2100     | 0.0685        | -               |
| 0.3330  | 2150     | 0.0008        | -               |
| 0.3408  | 2200     | 0.0           | -               |
| 0.3485  | 2250     | 0.0004        | -               |
| 0.3563  | 2300     | 0.0004        | -               |
| 0.3640  | 2350     | 0.0002        | -               |
| 0.3717  | 2400     | 0.0001        | -               |
| 0.3795  | 2450     | 0.0004        | -               |
| 0.3872  | 2500     | 0.0004        | -               |
| 0.3950  | 2550     | 0.0001        | -               |
| 0.4027  | 2600     | 0.0001        | -               |
| 0.4105  | 2650     | 0.0001        | -               |
| 0.4182  | 2700     | 0.0005        | -               |
| 0.4260  | 2750     | 0.0002        | -               |
| 0.4337  | 2800     | 0.0001        | -               |
| 0.4414  | 2850     | 0.0003        | -               |
| 0.4492  | 2900     | 0.0005        | -               |
| 0.4569  | 2950     | 0.0014        | -               |
| 0.4647  | 3000     | 0.0001        | -               |
| 0.4724  | 3050     | 0.0001        | -               |
| 0.4802  | 3100     | 0.0002        | -               |
| 0.4879  | 3150     | 0.0           | -               |
| 0.4957  | 3200     | 0.0006        | -               |
| 0.5034  | 3250     | 0.0           | -               |
| 0.5112  | 3300     | 0.0           | -               |
| 0.5189  | 3350     | 0.0002        | -               |
| 0.5266  | 3400     | 0.0001        | -               |
| 0.5344  | 3450     | 0.0006        | -               |
| 0.5421  | 3500     | 0.0002        | -               |
| 0.5499  | 3550     | 0.0001        | -               |
| 0.5576  | 3600     | 0.0001        | -               |
| 0.5654  | 3650     | 0.0001        | -               |
| 0.5731  | 3700     | 0.0           | -               |
| 0.5809  | 3750     | 0.0002        | -               |
| 0.5886  | 3800     | 0.0           | -               |
| 0.5963  | 3850     | 0.0044        | -               |
| 0.6041  | 3900     | 0.0002        | -               |
| 0.6118  | 3950     | 0.0001        | -               |
| 0.6196  | 4000     | 0.0003        | -               |
| 0.6273  | 4050     | 0.0005        | -               |
| 0.6351  | 4100     | 0.0002        | -               |
| 0.6428  | 4150     | 0.0           | -               |
| 0.6506  | 4200     | 0.0003        | -               |
| 0.6583  | 4250     | 0.0           | -               |
| 0.6660  | 4300     | 0.0001        | -               |
| 0.6738  | 4350     | 0.0           | -               |
| 0.6815  | 4400     | 0.0008        | -               |
| 0.6893  | 4450     | 0.0           | -               |
| 0.6970  | 4500     | 0.0004        | -               |
| 0.7048  | 4550     | 0.0001        | -               |
| 0.7125  | 4600     | 0.0           | -               |
| 0.7203  | 4650     | 0.0           | -               |
| 0.7280  | 4700     | 0.0           | -               |
| 0.7357  | 4750     | 0.0001        | -               |
| 0.7435  | 4800     | 0.0001        | -               |
| 0.7512  | 4850     | 0.001         | -               |
| 0.7590  | 4900     | 0.0001        | -               |
| 0.7667  | 4950     | 0.0           | -               |
| 0.7745  | 5000     | 0.0001        | -               |
| 0.7822  | 5050     | 0.0           | -               |
| 0.7900  | 5100     | 0.0018        | -               |
| 0.7977  | 5150     | 0.0001        | -               |
| 0.8055  | 5200     | 0.0           | -               |
| 0.8132  | 5250     | 0.0003        | -               |
| 0.8209  | 5300     | 0.0003        | -               |
| 0.8287  | 5350     | 0.0003        | -               |
| 0.8364  | 5400     | 0.0001        | -               |
| 0.8442  | 5450     | 0.0001        | -               |
| 0.8519  | 5500     | 0.0001        | -               |
| 0.8597  | 5550     | 0.0001        | -               |
| 0.8674  | 5600     | 0.0001        | -               |
| 0.8752  | 5650     | 0.0           | -               |
| 0.8829  | 5700     | 0.0003        | -               |
| 0.8906  | 5750     | 0.0003        | -               |
| 0.8984  | 5800     | 0.0001        | -               |
| 0.9061  | 5850     | 0.0001        | -               |
| 0.9139  | 5900     | 0.0002        | -               |
| 0.9216  | 5950     | 0.0           | -               |
| 0.9294  | 6000     | 0.0001        | -               |
| 0.9371  | 6050     | 0.0           | -               |
| 0.9449  | 6100     | 0.0           | -               |
| 0.9526  | 6150     | 0.0001        | -               |
| 0.9603  | 6200     | 0.0           | -               |
| 0.9681  | 6250     | 0.0001        | -               |
| 0.9758  | 6300     | 0.0002        | -               |
| 0.9836  | 6350     | 0.0           | -               |
| 0.9913  | 6400     | 0.0           | -               |
| 0.9991  | 6450     | 0.0002        | -               |
| **1.0** | **6456** | **-**         | **1.3837**      |
| 1.0068  | 6500     | 0.0001        | -               |
| 1.0146  | 6550     | 0.0001        | -               |
| 1.0223  | 6600     | 0.0002        | -               |
| 1.0300  | 6650     | 0.0001        | -               |
| 1.0378  | 6700     | 0.0005        | -               |
| 1.0455  | 6750     | 0.0001        | -               |
| 1.0533  | 6800     | 0.0001        | -               |
| 1.0610  | 6850     | 0.0           | -               |
| 1.0688  | 6900     | 0.0           | -               |
| 1.0765  | 6950     | 0.0009        | -               |
| 1.0843  | 7000     | 0.0           | -               |
| 1.0920  | 7050     | 0.0032        | -               |
| 1.0998  | 7100     | 0.0001        | -               |
| 1.1075  | 7150     | 0.0001        | -               |
| 1.1152  | 7200     | 0.0001        | -               |
| 1.1230  | 7250     | 0.0           | -               |
| 1.1307  | 7300     | 0.0001        | -               |
| 1.1385  | 7350     | 0.0           | -               |
| 1.1462  | 7400     | 0.0           | -               |
| 1.1540  | 7450     | 0.0002        | -               |
| 1.1617  | 7500     | 0.0           | -               |
| 1.1695  | 7550     | 0.0427        | -               |
| 1.1772  | 7600     | 0.0           | -               |
| 1.1849  | 7650     | 0.0           | -               |
| 1.1927  | 7700     | 0.0           | -               |
| 1.2004  | 7750     | 0.0002        | -               |
| 1.2082  | 7800     | 0.0           | -               |
| 1.2159  | 7850     | 0.0           | -               |
| 1.2237  | 7900     | 0.0           | -               |
| 1.2314  | 7950     | 0.0           | -               |
| 1.2392  | 8000     | 0.0001        | -               |
| 1.2469  | 8050     | 0.0           | -               |
| 1.2546  | 8100     | 0.0001        | -               |
| 1.2624  | 8150     | 0.0           | -               |
| 1.2701  | 8200     | 0.0           | -               |
| 1.2779  | 8250     | 0.0           | -               |
| 1.2856  | 8300     | 0.0           | -               |
| 1.2934  | 8350     | 0.0           | -               |
| 1.3011  | 8400     | 0.0           | -               |
| 1.3089  | 8450     | 0.0           | -               |
| 1.3166  | 8500     | 0.0           | -               |
| 1.3243  | 8550     | 0.0001        | -               |
| 1.3321  | 8600     | 0.0           | -               |
| 1.3398  | 8650     | 0.0002        | -               |
| 1.3476  | 8700     | 0.0           | -               |
| 1.3553  | 8750     | 0.0006        | -               |
| 1.3631  | 8800     | 0.0           | -               |
| 1.3708  | 8850     | 0.0           | -               |
| 1.3786  | 8900     | 0.0001        | -               |
| 1.3863  | 8950     | 0.0           | -               |
| 1.3941  | 9000     | 0.0001        | -               |
| 1.4018  | 9050     | 0.0           | -               |
| 1.4095  | 9100     | 0.0002        | -               |
| 1.4173  | 9150     | 0.0           | -               |
| 1.4250  | 9200     | 0.0           | -               |
| 1.4328  | 9250     | 0.0           | -               |
| 1.4405  | 9300     | 0.0           | -               |
| 1.4483  | 9350     | 0.0           | -               |
| 1.4560  | 9400     | 0.0           | -               |
| 1.4638  | 9450     | 0.0           | -               |
| 1.4715  | 9500     | 0.0           | -               |
| 1.4792  | 9550     | 0.0           | -               |
| 1.4870  | 9600     | 0.0           | -               |
| 1.4947  | 9650     | 0.0005        | -               |
| 1.5025  | 9700     | 0.0           | -               |
| 1.5102  | 9750     | 0.0001        | -               |
| 1.5180  | 9800     | 0.0001        | -               |
| 1.5257  | 9850     | 0.0001        | -               |
| 1.5335  | 9900     | 0.0           | -               |
| 1.5412  | 9950     | 0.0           | -               |
| 1.5489  | 10000    | 0.0           | -               |
| 1.5567  | 10050    | 0.0           | -               |
| 1.5644  | 10100    | 0.0001        | -               |
| 1.5722  | 10150    | 0.0           | -               |
| 1.5799  | 10200    | 0.0002        | -               |
| 1.5877  | 10250    | 0.0001        | -               |
| 1.5954  | 10300    | 0.0005        | -               |
| 1.6032  | 10350    | 0.0           | -               |
| 1.6109  | 10400    | 0.0           | -               |
| 1.6186  | 10450    | 0.0003        | -               |
| 1.6264  | 10500    | 0.0002        | -               |
| 1.6341  | 10550    | 0.0           | -               |
| 1.6419  | 10600    | 0.0           | -               |
| 1.6496  | 10650    | 0.0001        | -               |
| 1.6574  | 10700    | 0.0002        | -               |
| 1.6651  | 10750    | 0.0002        | -               |
| 1.6729  | 10800    | 0.0054        | -               |
| 1.6806  | 10850    | 0.0005        | -               |
| 1.6884  | 10900    | 0.0001        | -               |
| 1.6961  | 10950    | 0.0           | -               |
| 1.7038  | 11000    | 0.0           | -               |
| 1.7116  | 11050    | 0.0001        | -               |
| 1.7193  | 11100    | 0.0001        | -               |
| 1.7271  | 11150    | 0.0           | -               |
| 1.7348  | 11200    | 0.0001        | -               |
| 1.7426  | 11250    | 0.0           | -               |
| 1.7503  | 11300    | 0.0001        | -               |
| 1.7581  | 11350    | 0.0004        | -               |
| 1.7658  | 11400    | 0.0           | -               |
| 1.7735  | 11450    | 0.0001        | -               |
| 1.7813  | 11500    | 0.0           | -               |
| 1.7890  | 11550    | 0.0           | -               |
| 1.7968  | 11600    | 0.0           | -               |
| 1.8045  | 11650    | 0.0           | -               |
| 1.8123  | 11700    | 0.0001        | -               |
| 1.8200  | 11750    | 0.0002        | -               |
| 1.8278  | 11800    | 0.0           | -               |
| 1.8355  | 11850    | 0.0001        | -               |
| 1.8432  | 11900    | 0.0           | -               |
| 1.8510  | 11950    | 0.0001        | -               |
| 1.8587  | 12000    | 0.0           | -               |
| 1.8665  | 12050    | 0.0           | -               |
| 1.8742  | 12100    | 0.0           | -               |
| 1.8820  | 12150    | 0.0001        | -               |
| 1.8897  | 12200    | 0.0           | -               |
| 1.8975  | 12250    | 0.0           | -               |
| 1.9052  | 12300    | 0.0           | -               |
| 1.9129  | 12350    | 0.0           | -               |
| 1.9207  | 12400    | 0.0           | -               |
| 1.9284  | 12450    | 0.0           | -               |
| 1.9362  | 12500    | 0.0           | -               |
| 1.9439  | 12550    | 0.0003        | -               |
| 1.9517  | 12600    | 0.0001        | -               |
| 1.9594  | 12650    | 0.0           | -               |
| 1.9672  | 12700    | 0.0001        | -               |
| 1.9749  | 12750    | 0.0           | -               |
| 1.9827  | 12800    | 0.0           | -               |
| 1.9904  | 12850    | 0.0           | -               |
| 1.9981  | 12900    | 0.0001        | -               |
| 2.0     | 12912    | -             | 2.611           |
| 2.0059  | 12950    | 0.0           | -               |
| 2.0136  | 13000    | 0.0001        | -               |
| 2.0214  | 13050    | 0.0001        | -               |
| 2.0291  | 13100    | 0.0           | -               |
| 2.0369  | 13150    | 0.0           | -               |
| 2.0446  | 13200    | 0.0001        | -               |
| 2.0524  | 13250    | 0.0           | -               |
| 2.0601  | 13300    | 0.0002        | -               |
| 2.0678  | 13350    | 0.0           | -               |
| 2.0756  | 13400    | 0.0           | -               |
| 2.0833  | 13450    | 0.0001        | -               |
| 2.0911  | 13500    | 0.0001        | -               |
| 2.0988  | 13550    | 0.0003        | -               |
| 2.1066  | 13600    | 0.0           | -               |
| 2.1143  | 13650    | 0.0001        | -               |
| 2.1221  | 13700    | 0.0001        | -               |
| 2.1298  | 13750    | 0.0001        | -               |
| 2.1375  | 13800    | 0.0001        | -               |
| 2.1453  | 13850    | 0.0           | -               |
| 2.1530  | 13900    | 0.0           | -               |
| 2.1608  | 13950    | 0.0           | -               |
| 2.1685  | 14000    | 0.0           | -               |
| 2.1763  | 14050    | 0.0           | -               |
| 2.1840  | 14100    | 0.0001        | -               |
| 2.1918  | 14150    | 0.0           | -               |
| 2.1995  | 14200    | 0.0           | -               |
| 2.2072  | 14250    | 0.0001        | -               |
| 2.2150  | 14300    | 0.0           | -               |
| 2.2227  | 14350    | 0.0           | -               |
| 2.2305  | 14400    | 0.0004        | -               |
| 2.2382  | 14450    | 0.0001        | -               |
| 2.2460  | 14500    | 0.0           | -               |
| 2.2537  | 14550    | 0.0003        | -               |
| 2.2615  | 14600    | 0.0           | -               |
| 2.2692  | 14650    | 0.0001        | -               |
| 2.2770  | 14700    | 0.0001        | -               |
| 2.2847  | 14750    | 0.0           | -               |
| 2.2924  | 14800    | 0.0           | -               |
| 2.3002  | 14850    | 0.0005        | -               |
| 2.3079  | 14900    | 0.0           | -               |
| 2.3157  | 14950    | 0.0002        | -               |
| 2.3234  | 15000    | 0.0           | -               |
| 2.3312  | 15050    | 0.0           | -               |
| 2.3389  | 15100    | 0.0001        | -               |
| 2.3467  | 15150    | 0.0001        | -               |
| 2.3544  | 15200    | 0.0002        | -               |
| 2.3621  | 15250    | 0.0001        | -               |
| 2.3699  | 15300    | 0.0           | -               |
| 2.3776  | 15350    | 0.0           | -               |
| 2.3854  | 15400    | 0.0002        | -               |
| 2.3931  | 15450    | 0.0003        | -               |
| 2.4009  | 15500    | 0.0           | -               |
| 2.4086  | 15550    | 0.0           | -               |
| 2.4164  | 15600    | 0.0           | -               |
| 2.4241  | 15650    | 0.0001        | -               |
| 2.4318  | 15700    | 0.0           | -               |
| 2.4396  | 15750    | 0.0           | -               |
| 2.4473  | 15800    | 0.0002        | -               |
| 2.4551  | 15850    | 0.0           | -               |
| 2.4628  | 15900    | 0.0           | -               |
| 2.4706  | 15950    | 0.0           | -               |
| 2.4783  | 16000    | 0.0           | -               |
| 2.4861  | 16050    | 0.0001        | -               |
| 2.4938  | 16100    | 0.0           | -               |
| 2.5015  | 16150    | 0.0           | -               |
| 2.5093  | 16200    | 0.0           | -               |
| 2.5170  | 16250    | 0.0           | -               |
| 2.5248  | 16300    | 0.0           | -               |
| 2.5325  | 16350    | 0.0           | -               |
| 2.5403  | 16400    | 0.0           | -               |
| 2.5480  | 16450    | 0.0           | -               |
| 2.5558  | 16500    | 0.0           | -               |
| 2.5635  | 16550    | 0.0001        | -               |
| 2.5713  | 16600    | 0.0           | -               |
| 2.5790  | 16650    | 0.0           | -               |
| 2.5867  | 16700    | 0.0           | -               |
| 2.5945  | 16750    | 0.0           | -               |
| 2.6022  | 16800    | 0.0009        | -               |
| 2.6100  | 16850    | 0.0001        | -               |
| 2.6177  | 16900    | 0.0           | -               |
| 2.6255  | 16950    | 0.0001        | -               |
| 2.6332  | 17000    | 0.0           | -               |
| 2.6410  | 17050    | 0.0           | -               |
| 2.6487  | 17100    | 0.0001        | -               |
| 2.6564  | 17150    | 0.0           | -               |
| 2.6642  | 17200    | 0.0           | -               |
| 2.6719  | 17250    | 0.0           | -               |
| 2.6797  | 17300    | 0.0           | -               |
| 2.6874  | 17350    | 0.0004        | -               |
| 2.6952  | 17400    | 0.0           | -               |
| 2.7029  | 17450    | 0.0           | -               |
| 2.7107  | 17500    | 0.0           | -               |
| 2.7184  | 17550    | 0.0           | -               |
| 2.7261  | 17600    | 0.0           | -               |
| 2.7339  | 17650    | 0.0           | -               |
| 2.7416  | 17700    | 0.0001        | -               |
| 2.7494  | 17750    | 0.0           | -               |
| 2.7571  | 17800    | 0.0           | -               |
| 2.7649  | 17850    | 0.0001        | -               |
| 2.7726  | 17900    | 0.0           | -               |
| 2.7804  | 17950    | 0.0001        | -               |
| 2.7881  | 18000    | 0.0001        | -               |
| 2.7958  | 18050    | 0.0           | -               |
| 2.8036  | 18100    | 0.0           | -               |
| 2.8113  | 18150    | 0.0           | -               |
| 2.8191  | 18200    | 0.0           | -               |
| 2.8268  | 18250    | 0.0           | -               |
| 2.8346  | 18300    | 0.0001        | -               |
| 2.8423  | 18350    | 0.0           | -               |
| 2.8501  | 18400    | 0.0           | -               |
| 2.8578  | 18450    | 0.0           | -               |
| 2.8656  | 18500    | 0.0           | -               |
| 2.8733  | 18550    | 0.0           | -               |
| 2.8810  | 18600    | 0.0           | -               |
| 2.8888  | 18650    | 0.0           | -               |
| 2.8965  | 18700    | 0.0           | -               |
| 2.9043  | 18750    | 0.0           | -               |
| 2.9120  | 18800    | 0.0001        | -               |
| 2.9198  | 18850    | 0.0           | -               |
| 2.9275  | 18900    | 0.0           | -               |
| 2.9353  | 18950    | 0.0           | -               |
| 2.9430  | 19000    | 0.0           | -               |
| 2.9507  | 19050    | 0.0           | -               |
| 2.9585  | 19100    | 0.0           | -               |
| 2.9662  | 19150    | 0.0           | -               |
| 2.9740  | 19200    | 0.0           | -               |
| 2.9817  | 19250    | 0.0003        | -               |
| 2.9895  | 19300    | 0.0001        | -               |
| 2.9972  | 19350    | 0.0           | -               |
| 3.0     | 19368    | -             | 2.0845          |
| 3.0050  | 19400    | 0.0           | -               |
| 3.0127  | 19450    | 0.0001        | -               |
| 3.0204  | 19500    | 0.0           | -               |
| 3.0282  | 19550    | 0.0           | -               |
| 3.0359  | 19600    | 0.0           | -               |
| 3.0437  | 19650    | 0.0           | -               |
| 3.0514  | 19700    | 0.0           | -               |
| 3.0592  | 19750    | 0.0           | -               |
| 3.0669  | 19800    | 0.0001        | -               |
| 3.0747  | 19850    | 0.0           | -               |
| 3.0824  | 19900    | 0.0           | -               |
| 3.0901  | 19950    | 0.0001        | -               |
| 3.0979  | 20000    | 0.0           | -               |
| 3.1056  | 20050    | 0.0           | -               |
| 3.1134  | 20100    | 0.0           | -               |
| 3.1211  | 20150    | 0.0001        | -               |
| 3.1289  | 20200    | 0.0           | -               |
| 3.1366  | 20250    | 0.0           | -               |
| 3.1444  | 20300    | 0.0           | -               |
| 3.1521  | 20350    | 0.0           | -               |
| 3.1599  | 20400    | 0.0           | -               |
| 3.1676  | 20450    | 0.0001        | -               |
| 3.1753  | 20500    | 0.0           | -               |
| 3.1831  | 20550    | 0.0001        | -               |
| 3.1908  | 20600    | 0.0           | -               |
| 3.1986  | 20650    | 0.0           | -               |
| 3.2063  | 20700    | 0.0           | -               |
| 3.2141  | 20750    | 0.0           | -               |
| 3.2218  | 20800    | 0.0           | -               |
| 3.2296  | 20850    | 0.0003        | -               |
| 3.2373  | 20900    | 0.0           | -               |
| 3.2450  | 20950    | 0.0           | -               |
| 3.2528  | 21000    | 0.0           | -               |
| 3.2605  | 21050    | 0.0           | -               |
| 3.2683  | 21100    | 0.0001        | -               |
| 3.2760  | 21150    | 0.0001        | -               |
| 3.2838  | 21200    | 0.0           | -               |
| 3.2915  | 21250    | 0.0           | -               |
| 3.2993  | 21300    | 0.0           | -               |
| 3.3070  | 21350    | 0.0           | -               |
| 3.3147  | 21400    | 0.0           | -               |
| 3.3225  | 21450    | 0.0001        | -               |
| 3.3302  | 21500    | 0.0           | -               |
| 3.3380  | 21550    | 0.0           | -               |
| 3.3457  | 21600    | 0.0           | -               |
| 3.3535  | 21650    | 0.0           | -               |
| 3.3612  | 21700    | 0.0           | -               |
| 3.3690  | 21750    | 0.0           | -               |
| 3.3767  | 21800    | 0.0           | -               |
| 3.3844  | 21850    | 0.0           | -               |
| 3.3922  | 21900    | 0.0001        | -               |
| 3.3999  | 21950    | 0.0           | -               |
| 3.4077  | 22000    | 0.0           | -               |
| 3.4154  | 22050    | 0.0001        | -               |
| 3.4232  | 22100    | 0.0           | -               |
| 3.4309  | 22150    | 0.0001        | -               |
| 3.4387  | 22200    | 0.0           | -               |
| 3.4464  | 22250    | 0.0           | -               |
| 3.4542  | 22300    | 0.0           | -               |
| 3.4619  | 22350    | 0.0001        | -               |
| 3.4696  | 22400    | 0.0           | -               |
| 3.4774  | 22450    | 0.0           | -               |
| 3.4851  | 22500    | 0.0           | -               |
| 3.4929  | 22550    | 0.0001        | -               |
| 3.5006  | 22600    | 0.0002        | -               |
| 3.5084  | 22650    | 0.0001        | -               |
| 3.5161  | 22700    | 0.0           | -               |
| 3.5239  | 22750    | 0.0001        | -               |
| 3.5316  | 22800    | 0.0           | -               |
| 3.5393  | 22850    | 0.0           | -               |
| 3.5471  | 22900    | 0.0001        | -               |
| 3.5548  | 22950    | 0.0           | -               |
| 3.5626  | 23000    | 0.0           | -               |
| 3.5703  | 23050    | 0.0           | -               |
| 3.5781  | 23100    | 0.0           | -               |
| 3.5858  | 23150    | 0.0001        | -               |
| 3.5936  | 23200    | 0.0           | -               |
| 3.6013  | 23250    | 0.0001        | -               |
| 3.6090  | 23300    | 0.0001        | -               |
| 3.6168  | 23350    | 0.0           | -               |
| 3.6245  | 23400    | 0.0003        | -               |
| 3.6323  | 23450    | 0.0           | -               |
| 3.6400  | 23500    | 0.0           | -               |
| 3.6478  | 23550    | 0.0001        | -               |
| 3.6555  | 23600    | 0.0           | -               |
| 3.6633  | 23650    | 0.0           | -               |
| 3.6710  | 23700    | 0.0           | -               |
| 3.6787  | 23750    | 0.0001        | -               |
| 3.6865  | 23800    | 0.0           | -               |
| 3.6942  | 23850    | 0.0001        | -               |
| 3.7020  | 23900    | 0.0002        | -               |
| 3.7097  | 23950    | 0.0           | -               |
| 3.7175  | 24000    | 0.0           | -               |
| 3.7252  | 24050    | 0.0           | -               |
| 3.7330  | 24100    | 0.0           | -               |
| 3.7407  | 24150    | 0.0001        | -               |
| 3.7485  | 24200    | 0.0           | -               |
| 3.7562  | 24250    | 0.0           | -               |
| 3.7639  | 24300    | 0.0           | -               |
| 3.7717  | 24350    | 0.0           | -               |
| 3.7794  | 24400    | 0.0           | -               |
| 3.7872  | 24450    | 0.0           | -               |
| 3.7949  | 24500    | 0.0001        | -               |
| 3.8027  | 24550    | 0.0001        | -               |
| 3.8104  | 24600    | 0.0           | -               |
| 3.8182  | 24650    | 0.0           | -               |
| 3.8259  | 24700    | 0.0           | -               |
| 3.8336  | 24750    | 0.0           | -               |
| 3.8414  | 24800    | 0.0001        | -               |
| 3.8491  | 24850    | 0.0           | -               |
| 3.8569  | 24900    | 0.0           | -               |
| 3.8646  | 24950    | 0.0           | -               |
| 3.8724  | 25000    | 0.0           | -               |
| 3.8801  | 25050    | 0.0           | -               |
| 3.8879  | 25100    | 0.0           | -               |
| 3.8956  | 25150    | 0.0001        | -               |
| 3.9033  | 25200    | 0.0           | -               |
| 3.9111  | 25250    | 0.0002        | -               |
| 3.9188  | 25300    | 0.0001        | -               |
| 3.9266  | 25350    | 0.0           | -               |
| 3.9343  | 25400    | 0.0           | -               |
| 3.9421  | 25450    | 0.0           | -               |
| 3.9498  | 25500    | 0.0001        | -               |
| 3.9576  | 25550    | 0.0           | -               |
| 3.9653  | 25600    | 0.0           | -               |
| 3.9730  | 25650    | 0.0001        | -               |
| 3.9808  | 25700    | 0.0           | -               |
| 3.9885  | 25750    | 0.0           | -               |
| 3.9963  | 25800    | 0.0           | -               |
| 4.0     | 25824    | -             | 2.3576          |

* The bold row denotes the saved checkpoint.
### Framework Versions
- Python: 3.10.12
- SetFit: 1.0.3
- Sentence Transformers: 3.0.1
- Transformers: 4.39.0
- PyTorch: 2.3.0+cu121
- Datasets: 2.20.0
- Tokenizers: 0.15.2

## 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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