Model: aloobun/indic-mxbai-L8-embed
Author: aloobun
Pipeline: sentence-similarity
Library: sentence-transformers
Tags: sentence-transformers, safetensors, bert, sentence-similarity, feature-extraction, generated_from_trainer, dataset_size:112855, loss:MSELoss, indic, bn, gu, hi, kn, ml, mr, ta, te, dataset:aloobun/indic-parallel-sentences-talks, arxiv:1908.10084, arxiv:2004.09813, base_model:aloobun/d-mxbai-L8-embed, base_model:finetune:aloobun/d-mxbai-L8-embed, license:apache-2.0, model-index, text-embeddings-inference, endpoints_compatible, region:us
Base models (finetune): id: aloobun/d-mxbai-L8-embed
Card metadata: language: bn, gu, hi, kn, ml, mr, ta, te
tags: sentence-transformers, sentence-similarity, feature-extraction, generated_from_trainer, dataset_size:112855, loss:MSELoss, indic
base_model: aloobun/d-mxbai-L8-embed
widget: source_sentence: (Laughter) And I've already hinted what that something is.
sentences: हे मजेशीर आहे, मी ट्विटर आणि फेसबुकवर विचारले असे की, "तुम्ही अगतिकतेची व्याख्या कशी कराल? तुम्हाला कशामुळे अगतिक वाटते?", (हशा) आणि मी आधीच थोडीशी कल्पना दिली आहे ते काय करावे लागेल त्याबद्दल., तर मी जेव्हा ह्या दालनात नजर फिरवितो माणसांवर, ज्यांनी मिळवलंय, किंवा मिळवायच्या मार्गावर आहेत, लक्षणीय यश, मी त्यांना हे लक्षात ठेवायला सांगतो: वाट पाहू नका., source_sentence: I no longer try to be right; I choose to be happy.
sentences: এটি একটি অসাধারণ ঘনটা এবং এক অদ্ভুত অনুধাবন।, কেন এই ধারণাটা ছড়িয়ে গেল?, আমি সুখে থাকাকেই বেছে নিয়েছি।, source_sentence: And if tempers are still too high, then they send someone off to visit some relatives, as a cooling-off period.
sentences: और यदि तब भी गुस्सा शांत न हो, तो वो किसी को अपने रिश्तेदारों से मिलने भेज देते हैं शांत होने के लिये।, और वे तुम्हे गलत समय पर बाधित करते रहते है जब तुम अच मैं कुच करने कि कोशिश कर रहे होते हो जिसके लिये वे तुम्हे भुगतान करते है वे तुमको बधित करते हैं।, इस प्रयोग का आखिरी सवाल था: कैसे आप अपने जीवन से दूसरों पर सकारात्मक प्रभाव डालेंगे?, source_sentence: I see, I see one way in the back.
sentences: ಸ್ಟಾಂಡರ್ಡ್ ಚಾರ್ಟರ್ಡ್ 140 ಮಿಲಿಯನ್ ತಂದಿದೆ., ನಗರಗಳಲ್ಲಂತೂ ಶೇಕಡಾ ೮೦ರಷ್ಟು ಮಕ್ಕಳು ಕಾಲೇಜಿಗೆ ಹೋಗುತ್ತಾರೆ., ಇನ್ನು ಯಾರಾದರೂ? ನನಗೆ ಕಾಣಿಸುತ್ತಿದೆ, ಅಲ್ಲಿ..ಹಿಂದೆ.. ಒಂದು ಕೈ ಕಾಣಿಸುತ್ತಿದೆ., source_sentence: Whenever it rains, magically, mushrooms appear overnight.
sentences: ಈ ವಿಷಯವನ್ನು ಅವರು ಮುಚ್ಚಿಟ್ಟರು, ಆದರೆ ಇತರರಿಗೆ ಬೇಗನೇ ತಿಳಿಯಿತು., ಮಳೆಯಾದಾಗೆಲ್ಲ, ಮನಮೋಹಕವಾಗಿ, ಅಣಬೆಗಳು ಒಂದು ರಾತ್ರಿಯ  ವೇಳೆಯಲ್ಲಿ ಕಾಣಿಸಿಕೊಳ್ಳುತ್ತವೆ., ಪ್ರೇಕ್ಷಕ: 1947 ಎಬಿ: 1947, ಯಾವ ತಿಂಗಳು?
datasets: aloobun/indic-parallel-sentences-talks
pipeline_tag: sentence-similarity
library_name: sentence-transformers
metrics: negative_mse, src2trg_accuracy, trg2src_accuracy, mean_accuracy, pearson_cosine, spearman_cosine
model-index: name: SentenceTransformer based on aloobun/d-mxbai-L8-embed
results: task: type: knowledge-distillation
name: Knowledge Distillation
dataset: name: en mr
type: en-mr
metrics: type: negative_mse
value: -14.405468106269836
name: Negative Mse
verified: no, task: type: translation
name: Translation
dataset: name: en mr
type: en-mr
metrics: type: src2trg_accuracy
value: 0.324
name: Src2Trg Accuracy
verified: no, type: trg2src_accuracy
value: 0.174
name: Trg2Src Accuracy
verified: no, type: mean_accuracy
value: 0.249
name: Mean Accuracy
verified: no, task: type: semantic-similarity
name: Semantic Similarity
dataset: name: sts17 en mr test
type: sts17-en-mr-test
metrics: type: pearson_cosine
value: 0.21811289256702704
name: Pearson Cosine
verified: no, type: spearman_cosine
value: 0.22533360893418355
name: Spearman Cosine
verified: no, task: type: knowledge-distillation
name: Knowledge Distillation
dataset: name: en hi
type: en-hi
metrics: type: negative_mse
value: -14.047445356845856
name: Negative Mse
verified: no, task: type: translation
name: Translation
dataset: name: en hi
type: en-hi
metrics: type: src2trg_accuracy
value: 0.465
name: Src2Trg Accuracy
verified: no, type: trg2src_accuracy
value: 0.244
name: Trg2Src Accuracy
verified: no, type: mean_accuracy
value: 0.35450000000000004
name: Mean Accuracy
verified: no, task: type: semantic-similarity
name: Semantic Similarity
dataset: name: sts17 en hi test
type: sts17-en-hi-test
metrics: type: pearson_cosine
value: 0.08483694965794362
name: Pearson Cosine
verified: no, type: spearman_cosine
value: 0.13404452326754046
name: Spearman Cosine
verified: no, task: type: knowledge-distillation
name: Knowledge Distillation
dataset: name: en bn
type: en-bn
metrics: type: negative_mse
value: -15.71638137102127
name: Negative Mse
verified: no, task: type: translation
name: Translation
dataset: name: en bn
type: en-bn
metrics: type: src2trg_accuracy
value: 0.242
name: Src2Trg Accuracy
verified: no, type: trg2src_accuracy
value: 0.081
name: Trg2Src Accuracy
verified: no, type: mean_accuracy
value: 0.1615
name: Mean Accuracy
verified: no, task: type: semantic-similarity
name: Semantic Similarity
dataset: name: sts17 en bn test
type: sts17-en-bn-test
metrics: type: pearson_cosine
value: 0.14785129719314127
name: Pearson Cosine
verified: no, type: spearman_cosine
value: 0.1830075106480045
name: Spearman Cosine
verified: no, task: type: knowledge-distillation
name: Knowledge Distillation
dataset: name: en gu
type: en-gu
metrics: type: negative_mse
value: -16.396714746952057
name: Negative Mse
verified: no, task: type: translation
name: Translation
dataset: name: en gu
type: en-gu
metrics: type: src2trg_accuracy
value: 0.04
name: Src2Trg Accuracy
verified: no, type: trg2src_accuracy
value: 0.017
name: Trg2Src Accuracy
verified: no, type: mean_accuracy
value: 0.0285
name: Mean Accuracy
verified: no, task: type: semantic-similarity
name: Semantic Similarity
dataset: name: sts17 en gu test
type: sts17-en-gu-test
metrics: type: pearson_cosine
value: 0.08746107622701571
name: Pearson Cosine
verified: no, type: spearman_cosine
value: 0.11731440991672663
name: Spearman Cosine
verified: no, task: type: knowledge-distillation
name: Knowledge Distillation
dataset: name: en ta
type: en-ta
metrics: type: negative_mse
value: -16.221003234386444
name: Negative Mse
verified: no, task: type: translation
name: Translation
dataset: name: en ta
type: en-ta
metrics: type: src2trg_accuracy
value: 0.102
name: Src2Trg Accuracy
verified: no, type: trg2src_accuracy
value: 0.04
name: Trg2Src Accuracy
verified: no, type: mean_accuracy
value: 0.071
name: Mean Accuracy
verified: no, task: type: semantic-similarity
name: Semantic Similarity
dataset: name: sts17 en ta test
type: sts17-en-ta-test
metrics: type: pearson_cosine
value: -0.02863897450386144
name: Pearson Cosine
verified: no, type: spearman_cosine
value: -0.039475796340022885
name: Spearman Cosine
verified: no, task: type: knowledge-distillation
name: Knowledge Distillation
dataset: name: en kn
type: en-kn
metrics: type: negative_mse
value: -16.703946888446808
name: Negative Mse
verified: no, task: type: translation
name: Translation
dataset: name: en kn
type: en-kn
metrics: type: src2trg_accuracy
value: 0.117
name: Src2Trg Accuracy
verified: no, type: trg2src_accuracy
value: 0.068
name: Trg2Src Accuracy
verified: no, type: mean_accuracy
value: 0.0925
name: Mean Accuracy
verified: no, task: type: semantic-similarity
name: Semantic Similarity
dataset: name: sts17 en kn test
type: sts17-en-kn-test
metrics: type: pearson_cosine
value: 0.04635550247380243
name: Pearson Cosine
verified: no, type: spearman_cosine
value: 0.020029816999255046
name: Spearman Cosine
verified: no, task: type: knowledge-distillation
name: Knowledge Distillation
dataset: name: en te
type: en-te
metrics: type: negative_mse
value: -17.04743355512619
name: Negative Mse
verified: no, task: type: translation
name: Translation
dataset: name: en te
type: en-te
metrics: type: src2trg_accuracy
value: 0.075
name: Src2Trg Accuracy
verified: no, type: trg2src_accuracy
value: 0.025
name: Trg2Src Accuracy
verified: no, type: mean_accuracy
value: 0.05
name: Mean Accuracy
verified: no, task: type: semantic-similarity
name: Semantic Similarity
dataset: name: sts17 en te test
type: sts17-en-te-test
metrics: type: pearson_cosine
value: 0.12394140653755585
name: Pearson Cosine
verified: no, type: spearman_cosine
value: 0.19417699598729235
name: Spearman Cosine
verified: no, task: type: knowledge-distillation
name: Knowledge Distillation
dataset: name: en ml
type: en-ml
metrics: type: negative_mse
value: -17.274518311023712
name: Negative Mse
verified: no, task: type: translation
name: Translation
dataset: name: en ml
type: en-ml
metrics: type: src2trg_accuracy
value: 0.054
name: Src2Trg Accuracy
verified: no, type: trg2src_accuracy
value: 0.024
name: Trg2Src Accuracy
verified: no, type: mean_accuracy
value: 0.039
name: Mean Accuracy
verified: no, task: type: semantic-similarity
name: Semantic Similarity
dataset: name: sts17 en ml test
type: sts17-en-ml-test
metrics: type: pearson_cosine
value: 0.24086569602868083
name: Pearson Cosine
verified: no, type: spearman_cosine
value: 0.2717089217002832
name: Spearman Cosine
verified: no
license: apache-2.0
Likes: 0 | All-time downloads: 110
Created: 2024-12-19 16:43:56