metadata

base_model: sentence-transformers/paraphrase-mpnet-base-v2
library_name: setfit
metrics:
  - accuracy
pipeline_tag: text-classification
tags:
  - setfit
  - sentence-transformers
  - text-classification
  - generated_from_setfit_trainer
widget:
  - text: Why should companies invest in UX design?
  - text: Evaluate the efficiency of the current workflow.
  - text: I need a resume for a finance analyst.
  - text: Generate ideas for improving employee satisfaction.
  - text: Generate a campaign for increasing our Instagram followers.
inference: true
model-index:
  - name: SetFit with sentence-transformers/paraphrase-mpnet-base-v2
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: Unknown
          type: unknown
          split: test
        metrics:
          - type: accuracy
            value: 0.9977272727272727
            name: Accuracy

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

This is a SetFit model that can be used for Text Classification. This SetFit model uses sentence-transformers/paraphrase-mpnet-base-v2 as the Sentence Transformer embedding model. A LogisticRegression instance is used for classification.

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

Fine-tuning a Sentence Transformer with contrastive learning.
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-mpnet-base-v2
Classification head: a LogisticRegression instance
Maximum Sequence Length: 512 tokens
Number of Classes: 44 classes

Model Sources

Repository: SetFit on GitHub
Paper: Efficient Few-Shot Learning Without Prompts
Blogpost: SetFit: Efficient Few-Shot Learning Without Prompts

Model Labels

Label	Examples
analyze	'Analyze the results from the A/B testing.' 'Evaluate the effectiveness of the new strategy.' 'What are the key insights from the customer survey?'
analyze advantages	'Analyze the advantages of social media marketing for startups.' 'Analyze the advantages of electric vehicles over gas-powered cars.' 'What are the benefits of a plant-based diet for health?'
analyze best practices	'What are the industry standards for data security?' 'Evaluate best practices for customer service.' 'Analyze best practices for social media marketing.'
analyze business proposal	'Analyze the competitive analysis in the business plan.' 'Evaluate the team structure mentioned in the proposal.' 'What are the key points in the executive summary?'
analyze data	'What does the data tell us about user engagement?' 'Analyze the sales data for the last quarter.' 'Analyze the data to determine customer preferences.'
analyze data backup and recovery	'Evaluate the effectiveness of the backup strategy.' 'Analyze the current data backup procedures.' 'What are the risks associated with our data recovery plan?'
analyze data visualization	'What does this bar chart tell us about customer demographics?' 'Interpret the data in this line chart.' 'Analyze the distribution shown in this histogram.'
analyze feedback	'Analyze customer feedback from the recent survey.' 'Analyze the feedback received from the beta testers.' 'Evaluate the feedback from the focus group.'
analyze information	'What are the main points from the research findings?' 'Evaluate the information from the competitor analysis.' 'What conclusions can be drawn from the survey results?'
analyze information technology security policy	'Evaluate the risks mentioned in the security policy.' "Analyze the company's IT security policy." 'What are the strengths of our IT security measures?'
analyze job descriptions	'Analyze the job description for the new position.' 'What are the key responsibilities listed in the job description?' 'Evaluate the job description for inclusivity.'
analyze marketing campaign	'Evaluate the customer conversion rates from the Google Ads campaign.' 'What were the engagement rates for the spring sale campaign?' 'Assess the performance of the influencer marketing strategy.'
analyze packaging design	'What are the strengths and weaknesses of the packaging?' 'Evaluate the impact of packaging on brand perception.' 'Analyze the cost-effectiveness of the packaging design.'
analyze process	'What are the key steps in our product development process?' 'Evaluate the process for software deployment.' 'Analyze the process for onboarding new employees.'
analyze product description	'What are the strengths of this product description?' 'Evaluate the clarity of the product description.' 'Analyze the persuasiveness of the product features.'
analyze product rebranding	'What were the challenges faced during rebranding?' 'What are the key changes in the new branding?' 'Evaluate the customer response to the rebranding effort.'
analyze product recall	'Analyze the customer feedback after the recall.' 'What were the financial implications of the recall?' 'Evaluate the effectiveness of the recall process.'
analyze social media campaign	'Evaluate the reach and impressions of the LinkedIn posts.' 'Analyze the effectiveness of the Twitter campaign.' 'What improvements can be made to our social media campaigns?'
analyze time management	'Analyze how I can better prioritize my tasks.' 'Analyze my current time management techniques.' 'What are the weaknesses in my time management?'
analyze trends	'Analyze the social media trends influencing businesses.' 'What are the current trends in digital marketing?' 'Analyze the latest trends in the tech industry.'
analyze website concept	'Analyze the content strategy of the new website.' 'What are the key elements of a successful website concept?' 'Analyze the mobile responsiveness of the website design.'
bake	'Bake a loaf of banana bread.' 'How do I bake a cheesecake?' 'Bake a batch of brownies.'
define	"Define the term 'machine learning'." "What does 'SEO' stand for?" "Define 'data analytics'."
explain	"Explain the importance of cybersecurity in today's world." 'Explain how machine learning works.' 'Can you clarify what SEO involves?'
explain the importance of user experience design	'Explain how UX design improves accessibility.' 'Why is user experience design important for websites?' 'Why should companies invest in UX design?'
generate business proposal	'What is the format for a business proposal?' 'Generate a business proposal for a new product line.' 'Create a proposal for a partnership with another company.'
generate crisis communication plan	'Create a communication plan for a financial crisis.' 'Create a plan for communicating with stakeholders in a crisis.' 'Generate a plan for internal communication during a crisis.'
generate ideas	'Generate ideas for improving employee satisfaction.' 'Come up with ideas for our company’s anniversary event.' 'What are some unique selling points for our service?'
generate learning plan	'Create a learning plan for understanding machine learning concepts.' 'Create a plan for learning digital marketing skills.' 'What should be included in a learning plan for data science?'
generate product description	'Generate a product description for the new smartphone.' 'Create a detailed description of the latest software.' 'What should be included in a product description?'
generate product roadmap	'Create a roadmap for the new software development.' 'What should be included in a product roadmap?' 'Generate a product roadmap for customer feedback integration.'
generate project proposal	'What are the key elements of a project proposal?' 'What should be included in a project proposal?' 'Generate a proposal for a research project.'
generate recommendations	'Provide recommendations for streamlining operations.' 'Generate recommendations for improving customer service.' 'What are your recommendations for the new marketing strategy?'
generate resume	'I need a resume for a teaching position.' 'Generate a resume for a software engineer.' 'Generate a resume for a data scientist.'
generate social media campaign	"Create a campaign to highlight our company's sustainability efforts." 'Generate a campaign for increasing our Instagram followers.' 'I need a campaign plan for promoting our summer sale.'
generate template	'Can you make a template for job descriptions?' 'Create a template for a project proposal.' 'Generate a meeting agenda template.'
generate training program outline	'Generate a training program outline for new employees.' 'Generate an outline for diversity and inclusion training.' 'Create an outline for a leadership training program.'
learn a language	'How do I become fluent in Portuguese?' 'How can I practice English pronunciation?' 'What is the best way to learn Chinese characters?'
manage time	'How do I balance work and personal life?' 'Tips for managing time during exams.' 'How do I create a daily schedule?'
outline steps	'What are the steps to develop a training program?' 'Outline the steps to launch a new product.' 'Outline the steps to implement a new software system.'
provide general information	'Can you give me an overview of the new software?' "Give me general information about the industry's trends." 'What are the key points about the product launch?'
recommend	'What are the top destinations for a vacation?' 'What podcasts would you suggest for entrepreneurs?' 'Recommend a good book on data science.'
summarize advantages	'Summarize the advantages of using renewable energy.' 'Summarize the advantages of social media marketing.' 'What are the benefits of using project management software?'
summarize financial report	'Summarize the main findings of the quarterly financial report.' 'Provide a summary of the financial projections.' 'What are the key metrics in the financial summary?'

Evaluation

Metrics

Label	Accuracy
all	0.9977

Uses

Direct Use for Inference

First install the SetFit library:

pip install setfit

Then you can load this model and run inference.

from setfit import SetFitModel

# Download from the 🤗 Hub
model = SetFitModel.from_pretrained("nmlemus/setfit-paraphrase-mpnet-base-v2-surepath-chatgtp-dataset")
# Run inference
preds = model("I need a resume for a finance analyst.")

Training Details

Training Set Metrics

Training set	Min	Median	Max
Word count	3	7.8795	13

Label	Training Sample Count
analyze	10
analyze advantages	10
analyze best practices	10
analyze business proposal	10
analyze data	10
analyze data backup and recovery	10
analyze data visualization	10
analyze feedback	10
analyze information	10
analyze information technology security policy	10
analyze job descriptions	10
analyze marketing campaign	10
analyze packaging design	10
analyze process	10
analyze product description	10
analyze product rebranding	10
analyze product recall	10
analyze social media campaign	10
analyze time management	10
analyze trends	10
analyze website concept	10
bake	10
define	10
explain	10
explain the importance of user experience design	10
generate business proposal	10
generate crisis communication plan	10
generate ideas	10
generate learning plan	10
generate product description	10
generate product roadmap	10
generate project proposal	10
generate recommendations	10
generate resume	10
generate social media campaign	10
generate template	10
generate training program outline	10
learn a language	10
manage time	10
outline steps	10
provide general information	10
recommend	10
summarize advantages	10
summarize financial report	10

Training Hyperparameters

batch_size: (16, 16)
num_epochs: (4, 4)
max_steps: -1
sampling_strategy: oversampling
body_learning_rate: (2e-05, 1e-05)
head_learning_rate: 0.01
loss: CosineSimilarityLoss
distance_metric: cosine_distance
margin: 0.25
end_to_end: False
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
0.0001	1	0.1037	-
0.0042	50	0.1544	-
0.0085	100	0.1555	-
0.0127	150	0.0948	-
0.0169	200	0.1176	-
0.0211	250	0.1108	-
0.0254	300	0.1169	-
0.0296	350	0.1291	-
0.0338	400	0.1068	-
0.0381	450	0.1369	-
0.0423	500	0.0823	-
0.0465	550	0.0732	-
0.0507	600	0.1006	-
0.0550	650	0.0638	-
0.0592	700	0.0818	-
0.0634	750	0.0542	-
0.0677	800	0.039	-
0.0719	850	0.0497	-
0.0761	900	0.016	-
0.0803	950	0.021	-
0.0846	1000	0.0136	-
0.0888	1050	0.0353	-
0.0930	1100	0.0164	-
0.0973	1150	0.0123	-
0.1015	1200	0.0218	-
0.1057	1250	0.0845	-
0.1099	1300	0.0082	-
0.1142	1350	0.0385	-
0.1184	1400	0.0087	-
0.1226	1450	0.0133	-
0.1268	1500	0.0045	-
0.1311	1550	0.0054	-
0.1353	1600	0.0078	-
0.1395	1650	0.0068	-
0.1438	1700	0.0586	-
0.1480	1750	0.0173	-
0.1522	1800	0.0585	-
0.1564	1850	0.0052	-
0.1607	1900	0.0046	-
0.1649	1950	0.0021	-
0.1691	2000	0.0092	-
0.1734	2050	0.0027	-
0.1776	2100	0.0041	-
0.1818	2150	0.0053	-
0.1860	2200	0.0585	-
0.1903	2250	0.0034	-
0.1945	2300	0.0601	-
0.1987	2350	0.0061	-
0.2030	2400	0.0022	-
0.2072	2450	0.0037	-
0.2114	2500	0.0019	-
0.2156	2550	0.0012	-
0.2199	2600	0.0031	-
0.2241	2650	0.0028	-
0.2283	2700	0.0011	-
0.2326	2750	0.0019	-
0.2368	2800	0.0638	-
0.2410	2850	0.0018	-
0.2452	2900	0.0017	-
0.2495	2950	0.0021	-
0.2537	3000	0.0016	-
0.2579	3050	0.0013	-
0.2622	3100	0.0017	-
0.2664	3150	0.0101	-
0.2706	3200	0.0029	-
0.2748	3250	0.0013	-
0.2791	3300	0.002	-
0.2833	3350	0.0079	-
0.2875	3400	0.0013	-
0.2918	3450	0.001	-
0.2960	3500	0.0015	-
0.3002	3550	0.0013	-
0.3044	3600	0.0017	-
0.3087	3650	0.0012	-
0.3129	3700	0.0007	-
0.3171	3750	0.0019	-
0.3214	3800	0.0008	-
0.3256	3850	0.0008	-
0.3298	3900	0.0007	-
0.3340	3950	0.0007	-
0.3383	4000	0.001	-
0.3425	4050	0.0005	-
0.3467	4100	0.0008	-
0.3510	4150	0.0007	-
0.3552	4200	0.0014	-
0.3594	4250	0.0005	-
0.3636	4300	0.0008	-
0.3679	4350	0.0006	-
0.3721	4400	0.0011	-
0.3763	4450	0.0006	-
0.3805	4500	0.0007	-
0.3848	4550	0.0006	-
0.3890	4600	0.0003	-
0.3932	4650	0.0022	-
0.3975	4700	0.0007	-
0.4017	4750	0.0031	-
0.4059	4800	0.0013	-
0.4101	4850	0.0015	-
0.4144	4900	0.0017	-
0.4186	4950	0.0007	-
0.4228	5000	0.0006	-
0.4271	5050	0.0006	-
0.4313	5100	0.0013	-
0.4355	5150	0.0003	-
0.4397	5200	0.12	-
0.4440	5250	0.0005	-
0.4482	5300	0.0006	-
0.4524	5350	0.0016	-
0.4567	5400	0.0008	-
0.4609	5450	0.0118	-
0.4651	5500	0.0003	-
0.4693	5550	0.0542	-
0.4736	5600	0.0011	-
0.4778	5650	0.0004	-
0.4820	5700	0.001	-
0.4863	5750	0.0008	-
0.4905	5800	0.0008	-
0.4947	5850	0.0004	-
0.4989	5900	0.0008	-
0.5032	5950	0.0009	-
0.5074	6000	0.0005	-
0.5116	6050	0.0006	-
0.5159	6100	0.0012	-
0.5201	6150	0.0004	-
0.5243	6200	0.0005	-
0.5285	6250	0.0007	-
0.5328	6300	0.0009	-
0.5370	6350	0.0006	-
0.5412	6400	0.0007	-
0.5455	6450	0.0007	-
0.5497	6500	0.0003	-
0.5539	6550	0.0568	-
0.5581	6600	0.0006	-
0.5624	6650	0.0002	-
0.5666	6700	0.0006	-
0.5708	6750	0.0003	-
0.5751	6800	0.0003	-
0.5793	6850	0.0004	-
0.5835	6900	0.0006	-
0.5877	6950	0.0004	-
0.5920	7000	0.0004	-
0.5962	7050	0.0002	-
0.6004	7100	0.0002	-
0.6047	7150	0.001	-
0.6089	7200	0.0002	-
0.6131	7250	0.0004	-
0.6173	7300	0.0009	-
0.6216	7350	0.0003	-
0.6258	7400	0.0003	-
0.6300	7450	0.0018	-
0.6342	7500	0.0004	-
0.6385	7550	0.0035	-
0.6427	7600	0.0012	-
0.6469	7650	0.0005	-
0.6512	7700	0.0003	-
0.6554	7750	0.0003	-
0.6596	7800	0.0004	-
0.6638	7850	0.0004	-
0.6681	7900	0.0004	-
0.6723	7950	0.0003	-
0.6765	8000	0.0002	-
0.6808	8050	0.0002	-
0.6850	8100	0.0008	-
0.6892	8150	0.0003	-
0.6934	8200	0.0002	-
0.6977	8250	0.0003	-
0.7019	8300	0.0002	-
0.7061	8350	0.0024	-
0.7104	8400	0.0022	-
0.7146	8450	0.0004	-
0.7188	8500	0.0092	-
0.7230	8550	0.0002	-
0.7273	8600	0.0001	-
0.7315	8650	0.0002	-
0.7357	8700	0.0003	-
0.7400	8750	0.0005	-
0.7442	8800	0.0002	-
0.7484	8850	0.0005	-
0.7526	8900	0.0002	-
0.7569	8950	0.0002	-
0.7611	9000	0.0002	-
0.7653	9050	0.0002	-
0.7696	9100	0.0001	-
0.7738	9150	0.0002	-
0.7780	9200	0.0004	-
0.7822	9250	0.0003	-
0.7865	9300	0.0003	-
0.7907	9350	0.0002	-
0.7949	9400	0.0005	-
0.7992	9450	0.0002	-
0.8034	9500	0.0002	-
0.8076	9550	0.0017	-
0.8118	9600	0.0004	-
0.8161	9650	0.0003	-
0.8203	9700	0.0002	-
0.8245	9750	0.0002	-
0.8288	9800	0.0001	-
0.8330	9850	0.0001	-
0.8372	9900	0.0001	-
0.8414	9950	0.0005	-
0.8457	10000	0.0001	-
0.8499	10050	0.0001	-
0.8541	10100	0.0002	-
0.8584	10150	0.0002	-
0.8626	10200	0.0003	-
0.8668	10250	0.0003	-
0.8710	10300	0.0002	-
0.8753	10350	0.0002	-
0.8795	10400	0.001	-
0.8837	10450	0.0008	-
0.8879	10500	0.0005	-
0.8922	10550	0.0017	-
0.8964	10600	0.0606	-
0.9006	10650	0.0002	-
0.9049	10700	0.0003	-
0.9091	10750	0.0005	-
0.9133	10800	0.0008	-
0.9175	10850	0.0003	-
0.9218	10900	0.002	-
0.9260	10950	0.0003	-
0.9302	11000	0.0003	-
0.9345	11050	0.0003	-
0.9387	11100	0.0243	-
0.9429	11150	0.0016	-
0.9471	11200	0.021	-
0.9514	11250	0.0003	-
0.9556	11300	0.0006	-
0.9598	11350	0.0166	-
0.9641	11400	0.0014	-
0.9683	11450	0.0004	-
0.9725	11500	0.0006	-
0.9767	11550	0.0001	-
0.9810	11600	0.0002	-
0.9852	11650	0.0021	-
0.9894	11700	0.0004	-
0.9937	11750	0.0002	-
0.9979	11800	0.0003	-
1.0	11825	-	0.0019
1.0021	11850	0.0002	-
1.0063	11900	0.0002	-
1.0106	11950	0.0002	-
1.0148	12000	0.0002	-
1.0190	12050	0.0002	-
1.0233	12100	0.0002	-
1.0275	12150	0.0002	-
1.0317	12200	0.0002	-
1.0359	12250	0.0005	-
1.0402	12300	0.0002	-
1.0444	12350	0.0002	-
1.0486	12400	0.0004	-
1.0529	12450	0.0002	-
1.0571	12500	0.0002	-
1.0613	12550	0.0001	-
1.0655	12600	0.0001	-
1.0698	12650	0.0001	-
1.0740	12700	0.0001	-
1.0782	12750	0.0001	-
1.0825	12800	0.0002	-
1.0867	12850	0.0001	-
1.0909	12900	0.0002	-
1.0951	12950	0.0002	-
1.0994	13000	0.0002	-
1.1036	13050	0.0002	-
1.1078	13100	0.0001	-
1.1121	13150	0.0002	-
1.1163	13200	0.0236	-
1.1205	13250	0.0002	-
1.1247	13300	0.0001	-
1.1290	13350	0.0023	-
1.1332	13400	0.0003	-
1.1374	13450	0.0001	-
1.1416	13500	0.0003	-
1.1459	13550	0.0003	-
1.1501	13600	0.0004	-
1.1543	13650	0.0002	-
1.1586	13700	0.0002	-
1.1628	13750	0.0001	-
1.1670	13800	0.0001	-
1.1712	13850	0.0001	-
1.1755	13900	0.0001	-
1.1797	13950	0.0001	-
1.1839	14000	0.0001	-
1.1882	14050	0.0002	-
1.1924	14100	0.0002	-
1.1966	14150	0.0001	-
1.2008	14200	0.0002	-
1.2051	14250	0.0003	-
1.2093	14300	0.0001	-
1.2135	14350	0.0001	-
1.2178	14400	0.0002	-
1.2220	14450	0.001	-
1.2262	14500	0.0001	-
1.2304	14550	0.0001	-
1.2347	14600	0.0001	-
1.2389	14650	0.0002	-
1.2431	14700	0.0001	-
1.2474	14750	0.0002	-
1.2516	14800	0.0001	-
1.2558	14850	0.0001	-
1.2600	14900	0.0001	-
1.2643	14950	0.0002	-
1.2685	15000	0.0001	-
1.2727	15050	0.0061	-
1.2770	15100	0.0001	-
1.2812	15150	0.0004	-
1.2854	15200	0.0002	-
1.2896	15250	0.0002	-
1.2939	15300	0.0001	-
1.2981	15350	0.0001	-
1.3023	15400	0.0001	-
1.3066	15450	0.0002	-
1.3108	15500	0.0001	-
1.3150	15550	0.0001	-
1.3192	15600	0.002	-
1.3235	15650	0.0004	-
1.3277	15700	0.0001	-
1.3319	15750	0.0001	-
1.3362	15800	0.0002	-
1.3404	15850	0.0001	-
1.3446	15900	0.0001	-
1.3488	15950	0.0001	-
1.3531	16000	0.0002	-
1.3573	16050	0.0001	-
1.3615	16100	0.0003	-
1.3658	16150	0.0001	-
1.3700	16200	0.0001	-
1.3742	16250	0.0001	-
1.3784	16300	0.0001	-
1.3827	16350	0.0001	-
1.3869	16400	0.0001	-
1.3911	16450	0.0004	-
1.3953	16500	0.0002	-
1.3996	16550	0.0001	-
1.4038	16600	0.0001	-
1.4080	16650	0.0001	-
1.4123	16700	0.0001	-
1.4165	16750	0.0001	-
1.4207	16800	0.0001	-
1.4249	16850	0.0001	-
1.4292	16900	0.0001	-
1.4334	16950	0.0024	-
1.4376	17000	0.0001	-
1.4419	17050	0.0002	-
1.4461	17100	0.0001	-
1.4503	17150	0.0001	-
1.4545	17200	0.0001	-
1.4588	17250	0.0001	-
1.4630	17300	0.0606	-
1.4672	17350	0.0004	-
1.4715	17400	0.0001	-
1.4757	17450	0.0007	-
1.4799	17500	0.0001	-
1.4841	17550	0.0001	-
1.4884	17600	0.0001	-
1.4926	17650	0.0002	-
1.4968	17700	0.0015	-
1.5011	17750	0.0001	-
1.5053	17800	0.0001	-
1.5095	17850	0.0002	-
1.5137	17900	0.0002	-
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1.5222	18000	0.0001	-
1.5264	18050	0.0001	-
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1.5349	18150	0.0002	-
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1.5433	18250	0.0001	-
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1.5518	18350	0.0001	-
1.5560	18400	0.0002	-
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1.5729	18600	0.0001	-
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1.5814	18700	0.0002	-
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1.5983	18900	0.0009	-
1.6025	18950	0.0001	-
1.6068	19000	0.0002	-
1.6110	19050	0.0013	-
1.6152	19100	0.0001	-
1.6195	19150	0.0005	-
1.6237	19200	0.0001	-
1.6279	19250	0.0016	-
1.6321	19300	0.0001	-
1.6364	19350	0.0001	-
1.6406	19400	0.0015	-
1.6448	19450	0.0001	-
1.6490	19500	0.0001	-
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1.6575	19600	0.0001	-
1.6617	19650	0.0001	-
1.6660	19700	0.0001	-
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1.6744	19800	0.0001	-
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1.6829	19900	0.0001	-
1.6871	19950	0.0001	-
1.6913	20000	0.0001	-
1.6956	20050	0.0001	-
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1.7040	20150	0.0001	-
1.7082	20200	0.0001	-
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1.7252	20400	0.0001	-
1.7294	20450	0.0001	-
1.7336	20500	0.002	-
1.7378	20550	0.0001	-
1.7421	20600	0.0001	-
1.7463	20650	0.0001	-
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1.7548	20750	0.0001	-
1.7590	20800	0.0001	-
1.7632	20850	0.0001	-
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1.7717	20950	0.0002	-
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1.7801	21050	0.0004	-
1.7844	21100	0.0002	-
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1.7928	21200	0.0001	-
1.7970	21250	0.0001	-
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1.8055	21350	0.0001	-
1.8097	21400	0.0001	-
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1.8224	21550	0.0001	-
1.8266	21600	0.0001	-
1.8309	21650	0.0013	-
1.8351	21700	0.0002	-
1.8393	21750	0.0001	-
1.8436	21800	0.0001	-
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1.8520	21900	0.0001	-
1.8562	21950	0.0001	-
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1.8732	22150	0.0	-
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1.8816	22250	0.0001	-
1.8858	22300	0.0001	-
1.8901	22350	0.0001	-
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1.9070	22550	0.0001	-
1.9112	22600	0.0001	-
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1.9281	22800	0.0001	-
1.9323	22850	0.0001	-
1.9366	22900	0.0001	-
1.9408	22950	0.0	-
1.9450	23000	0.0016	-
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1.9535	23100	0.0002	-
1.9577	23150	0.0001	-
1.9619	23200	0.0001	-
1.9662	23250	0.0001	-
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1.9746	23350	0.0001	-
1.9789	23400	0.0001	-
1.9831	23450	0.0001	-
1.9873	23500	0.0016	-
1.9915	23550	0.0001	-
1.9958	23600	0.0001	-
2.0	23650	0.0001	0.0008
2.0042	23700	0.0001	-
2.0085	23750	0.0017	-
2.0127	23800	0.0001	-
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2.0211	23900	0.0001	-
2.0254	23950	0.0001	-
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2.0381	24100	0.0001	-
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2.0803	24600	0.0001	-
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2.1015	24850	0.0006	-
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2.1099	24950	0.0001	-
2.1142	25000	0.0004	-
2.1184	25050	0.0011	-
2.1226	25100	0.0001	-
2.1268	25150	0.0002	-
2.1311	25200	0.0003	-
2.1353	25250	0.0001	-
2.1395	25300	0.0014	-
2.1438	25350	0.0001	-
2.1480	25400	0.0002	-
2.1522	25450	0.0012	-
2.1564	25500	0.0001	-
2.1607	25550	0.0001	-
2.1649	25600	0.0002	-
2.1691	25650	0.0001	-
2.1734	25700	0.0001	-
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2.1818	25800	0.0001	-
2.1860	25850	0.0544	-
2.1903	25900	0.0001	-
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2.2030	26050	0.0001	-
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2.2156	26200	0.0002	-
2.2199	26250	0.0	-
2.2241	26300	0.0001	-
2.2283	26350	0.0002	-
2.2326	26400	0.0001	-
2.2368	26450	0.0001	-
2.2410	26500	0.0602	-
2.2452	26550	0.0022	-
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2.2579	26700	0.0002	-
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2.3256	27500	0.0001	-
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2.3340	27600	0.0001	-
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2.3425	27700	0.0015	-
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2.3510	27800	0.0002	-
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2.3594	27900	0.0001	-
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2.4059	28450	0.0001	-
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2.4271	28700	0.0001	-
2.4313	28750	0.0001	-
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2.4440	28900	0.0001	-
2.4482	28950	0.0001	-
2.4524	29000	0.0001	-
2.4567	29050	0.0021	-
2.4609	29100	0.0001	-
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2.4736	29250	0.0	-
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2.4820	29350	0.0002	-
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2.4947	29500	0.0002	-
2.4989	29550	0.0013	-
2.5032	29600	0.0001	-
2.5074	29650	0.0001	-
2.5116	29700	0.0001	-
2.5159	29750	0.0001	-
2.5201	29800	0.0015	-
2.5243	29850	0.0001	-
2.5285	29900	0.0001	-
2.5328	29950	0.0001	-
2.5370	30000	0.0002	-
2.5412	30050	0.0001	-
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2.5497	30150	0.0001	-
2.5539	30200	0.0001	-
2.5581	30250	0.0001	-
2.5624	30300	0.0002	-
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2.5835	30550	0.0001	-
2.5877	30600	0.0001	-
2.5920	30650	0.0001	-
2.5962	30700	0.0	-
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2.6047	30800	0.0001	-
2.6089	30850	0.0001	-
2.6131	30900	0.0001	-
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2.6216	31000	0.0001	-
2.6258	31050	0.0001	-
2.6300	31100	0.0001	-
2.6342	31150	0.0001	-
2.6385	31200	0.0001	-
2.6427	31250	0.0001	-
2.6469	31300	0.0001	-
2.6512	31350	0.0024	-
2.6554	31400	0.0001	-
2.6596	31450	0.0001	-
2.6638	31500	0.0025	-
2.6681	31550	0.0001	-
2.6723	31600	0.0001	-
2.6765	31650	0.0002	-
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2.6892	31800	0.0001	-
2.6934	31850	0.0001	-
2.6977	31900	0.0001	-
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2.7061	32000	0.0001	-
2.7104	32050	0.0001	-
2.7146	32100	0.0001	-
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2.7230	32200	0.0001	-
2.7273	32250	0.0001	-
2.7315	32300	0.0	-
2.7357	32350	0.0001	-
2.7400	32400	0.0001	-
2.7442	32450	0.0001	-
2.7484	32500	0.0001	-
2.7526	32550	0.0001	-
2.7569	32600	0.0016	-
2.7611	32650	0.0001	-
2.7653	32700	0.0001	-
2.7696	32750	0.0001	-
2.7738	32800	0.0001	-
2.7780	32850	0.0001	-
2.7822	32900	0.0001	-
2.7865	32950	0.0001	-
2.7907	33000	0.0001	-
2.7949	33050	0.0001	-
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2.8034	33150	0.0001	-
2.8076	33200	0.0001	-
2.8118	33250	0.0001	-
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2.8288	33450	0.0001	-
2.8330	33500	0.0	-
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2.8414	33600	0.0001	-
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2.8499	33700	0.0001	-
2.8541	33750	0.0016	-
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2.8626	33850	0.0001	-
2.8668	33900	0.0001	-
2.8710	33950	0.0001	-
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2.8795	34050	0.0001	-
2.8837	34100	0.0001	-
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2.8922	34200	0.0	-
2.8964	34250	0.0001	-
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2.9091	34400	0.0001	-
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2.9218	34550	0.0	-
2.9260	34600	0.0001	-
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2.9345	34700	0.0001	-
2.9387	34750	0.0155	-
2.9429	34800	0.0001	-
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2.9514	34900	0.0001	-
2.9556	34950	0.0001	-
2.9598	35000	0.0001	-
2.9641	35050	0.0	-
2.9683	35100	0.0018	-
2.9725	35150	0.0001	-
2.9767	35200	0.0001	-
2.9810	35250	0.0001	-
2.9852	35300	0.0001	-
2.9894	35350	0.0001	-
2.9937	35400	0.0001	-
2.9979	35450	0.0001	-
3.0	35475	-	0.0003
3.0021	35500	0.0001	-
3.0063	35550	0.0001	-
3.0106	35600	0.0022	-
3.0148	35650	0.0001	-
3.0190	35700	0.0001	-
3.0233	35750	0.0001	-
3.0275	35800	0.0	-
3.0317	35850	0.0019	-
3.0359	35900	0.0	-
3.0402	35950	0.0001	-
3.0444	36000	0.0001	-
3.0486	36050	0.0001	-
3.0529	36100	0.0	-
3.0571	36150	0.0	-
3.0613	36200	0.0001	-
3.0655	36250	0.0001	-
3.0698	36300	0.0001	-
3.0740	36350	0.0001	-
3.0782	36400	0.0001	-
3.0825	36450	0.0	-
3.0867	36500	0.0001	-
3.0909	36550	0.0001	-
3.0951	36600	0.0001	-
3.0994	36650	0.0001	-
3.1036	36700	0.0001	-
3.1078	36750	0.0	-
3.1121	36800	0.0001	-
3.1163	36850	0.0001	-
3.1205	36900	0.0	-
3.1247	36950	0.0001	-
3.1290	37000	0.0001	-
3.1332	37050	0.0001	-
3.1374	37100	0.0001	-
3.1416	37150	0.0001	-
3.1459	37200	0.0001	-
3.1501	37250	0.0001	-
3.1543	37300	0.0001	-
3.1586	37350	0.0001	-
3.1628	37400	0.0055	-
3.1670	37450	0.0	-
3.1712	37500	0.0001	-
3.1755	37550	0.0019	-
3.1797	37600	0.0001	-
3.1839	37650	0.0001	-
3.1882	37700	0.0	-
3.1924	37750	0.0	-
3.1966	37800	0.0001	-
3.2008	37850	0.0001	-
3.2051	37900	0.0	-
3.2093	37950	0.0001	-
3.2135	38000	0.0001	-
3.2178	38050	0.0001	-
3.2220	38100	0.0	-
3.2262	38150	0.0001	-
3.2304	38200	0.0	-
3.2347	38250	0.0001	-
3.2389	38300	0.0001	-
3.2431	38350	0.0	-
3.2474	38400	0.0001	-
3.2516	38450	0.0001	-
3.2558	38500	0.0	-
3.2600	38550	0.0	-
3.2643	38600	0.0	-
3.2685	38650	0.0017	-
3.2727	38700	0.0095	-
3.2770	38750	0.0001	-
3.2812	38800	0.0001	-
3.2854	38850	0.0	-
3.2896	38900	0.0001	-
3.2939	38950	0.0	-
3.2981	39000	0.0001	-
3.3023	39050	0.0	-
3.3066	39100	0.0001	-
3.3108	39150	0.0	-
3.3150	39200	0.0	-
3.3192	39250	0.0001	-
3.3235	39300	0.0001	-
3.3277	39350	0.0	-
3.3319	39400	0.0001	-
3.3362	39450	0.0001	-
3.3404	39500	0.0001	-
3.3446	39550	0.0	-
3.3488	39600	0.0001	-
3.3531	39650	0.0	-
3.3573	39700	0.0001	-
3.3615	39750	0.0001	-
3.3658	39800	0.0022	-
3.3700	39850	0.0001	-
3.3742	39900	0.0001	-
3.3784	39950	0.0	-
3.3827	40000	0.0	-
3.3869	40050	0.0	-
3.3911	40100	0.0001	-
3.3953	40150	0.0	-
3.3996	40200	0.0	-
3.4038	40250	0.0	-
3.4080	40300	0.0001	-
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3.4165	40400	0.0001	-
3.4207	40450	0.0	-
3.4249	40500	0.0001	-
3.4292	40550	0.0001	-
3.4334	40600	0.0001	-
3.4376	40650	0.0	-
3.4419	40700	0.0001	-
3.4461	40750	0.0	-
3.4503	40800	0.0	-
3.4545	40850	0.0	-
3.4588	40900	0.0	-
3.4630	40950	0.0001	-
3.4672	41000	0.0	-
3.4715	41050	0.0	-
3.4757	41100	0.0001	-
3.4799	41150	0.0016	-
3.4841	41200	0.0	-
3.4884	41250	0.0001	-
3.4926	41300	0.0	-
3.4968	41350	0.0001	-
3.5011	41400	0.0	-
3.5053	41450	0.0	-
3.5095	41500	0.0001	-
3.5137	41550	0.0	-
3.5180	41600	0.0	-
3.5222	41650	0.0019	-
3.5264	41700	0.0001	-
3.5307	41750	0.0001	-
3.5349	41800	0.0001	-
3.5391	41850	0.0001	-
3.5433	41900	0.0023	-
3.5476	41950	0.0001	-
3.5518	42000	0.0	-
3.5560	42050	0.0001	-
3.5603	42100	0.0001	-
3.5645	42150	0.0	-
3.5687	42200	0.0	-
3.5729	42250	0.0	-
3.5772	42300	0.0	-
3.5814	42350	0.0001	-
3.5856	42400	0.0	-
3.5899	42450	0.0	-
3.5941	42500	0.0	-
3.5983	42550	0.0	-
3.6025	42600	0.0001	-
3.6068	42650	0.0	-
3.6110	42700	0.0001	-
3.6152	42750	0.0001	-
3.6195	42800	0.0001	-
3.6237	42850	0.0001	-
3.6279	42900	0.0001	-
3.6321	42950	0.0	-
3.6364	43000	0.0	-
3.6406	43050	0.0	-
3.6448	43100	0.0001	-
3.6490	43150	0.0	-
3.6533	43200	0.0001	-
3.6575	43250	0.0001	-
3.6617	43300	0.0001	-
3.6660	43350	0.0001	-
3.6702	43400	0.0	-
3.6744	43450	0.0024	-
3.6786	43500	0.0	-
3.6829	43550	0.0001	-
3.6871	43600	0.002	-
3.6913	43650	0.0	-
3.6956	43700	0.0	-
3.6998	43750	0.0001	-
3.7040	43800	0.0001	-
3.7082	43850	0.0	-
3.7125	43900	0.0	-
3.7167	43950	0.0001	-
3.7209	44000	0.0	-
3.7252	44050	0.0001	-
3.7294	44100	0.0	-
3.7336	44150	0.0	-
3.7378	44200	0.0001	-
3.7421	44250	0.0	-
3.7463	44300	0.0	-
3.7505	44350	0.0001	-
3.7548	44400	0.0	-
3.7590	44450	0.0	-
3.7632	44500	0.0001	-
3.7674	44550	0.0	-
3.7717	44600	0.0	-
3.7759	44650	0.0	-
3.7801	44700	0.0022	-
3.7844	44750	0.0	-
3.7886	44800	0.0001	-
3.7928	44850	0.0	-
3.7970	44900	0.0001	-
3.8013	44950	0.0001	-
3.8055	45000	0.0	-
3.8097	45050	0.0	-
3.8140	45100	0.0	-
3.8182	45150	0.0	-
3.8224	45200	0.0	-
3.8266	45250	0.0	-
3.8309	45300	0.0001	-
3.8351	45350	0.0	-
3.8393	45400	0.0001	-
3.8436	45450	0.0001	-
3.8478	45500	0.0	-
3.8520	45550	0.0001	-
3.8562	45600	0.0001	-
3.8605	45650	0.0	-
3.8647	45700	0.0	-
3.8689	45750	0.0	-
3.8732	45800	0.0001	-
3.8774	45850	0.0015	-
3.8816	45900	0.0001	-
3.8858	45950	0.0	-
3.8901	46000	0.0	-
3.8943	46050	0.0001	-
3.8985	46100	0.0	-
3.9027	46150	0.0	-
3.9070	46200	0.0	-
3.9112	46250	0.0	-
3.9154	46300	0.0	-
3.9197	46350	0.0	-
3.9239	46400	0.0	-
3.9281	46450	0.0	-
3.9323	46500	0.0	-
3.9366	46550	0.0001	-
3.9408	46600	0.0001	-
3.9450	46650	0.0001	-
3.9493	46700	0.0001	-
3.9535	46750	0.0	-
3.9577	46800	0.0	-
3.9619	46850	0.0	-
3.9662	46900	0.0	-
3.9704	46950	0.0	-
3.9746	47000	0.0	-
3.9789	47050	0.0	-
3.9831	47100	0.0001	-
3.9873	47150	0.0001	-
3.9915	47200	0.0021	-
3.9958	47250	0.0	-
4.0	47300	0.0	0.0002

The bold row denotes the saved checkpoint.

Framework Versions

Python: 3.10.14
SetFit: 1.0.3
Sentence Transformers: 3.0.1
Transformers: 4.39.0
PyTorch: 2.4.0+cu121
Datasets: 2.20.0
Tokenizers: 0.15.2

Citation

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}
}