Update README.md
Browse files
README.md
CHANGED
|
@@ -4,6 +4,173 @@ language:
|
|
| 4 |
- en
|
| 5 |
tags:
|
| 6 |
- sparse sparsity quantized onnx embeddings int8
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 7 |
---
|
| 8 |
This is the quantized (INT8) ONNX variant of the [bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) embeddings model created with [DeepSparse Optimum](https://github.com/neuralmagic/optimum-deepsparse) for ONNX export/inference pipeline and Neural Magic's [Sparsify](https://github.com/neuralmagic/sparsify) for one-shot quantization.
|
| 9 |
|
|
|
|
| 4 |
- en
|
| 5 |
tags:
|
| 6 |
- sparse sparsity quantized onnx embeddings int8
|
| 7 |
+
model-index:
|
| 8 |
+
- name: bge-base-en-v1.5-quant
|
| 9 |
+
results:
|
| 10 |
+
- task:
|
| 11 |
+
type: Classification
|
| 12 |
+
dataset:
|
| 13 |
+
type: mteb/amazon_counterfactual
|
| 14 |
+
name: MTEB AmazonCounterfactualClassification (en)
|
| 15 |
+
config: en
|
| 16 |
+
split: test
|
| 17 |
+
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
|
| 18 |
+
metrics:
|
| 19 |
+
- type: accuracy
|
| 20 |
+
value: 76.16417910447761
|
| 21 |
+
- type: ap
|
| 22 |
+
value: 39.62965026785565
|
| 23 |
+
- type: f1
|
| 24 |
+
value: 70.30041589476463
|
| 25 |
+
- task:
|
| 26 |
+
type: Classification
|
| 27 |
+
dataset:
|
| 28 |
+
type: mteb/amazon_polarity
|
| 29 |
+
name: MTEB AmazonPolarityClassification
|
| 30 |
+
config: default
|
| 31 |
+
split: test
|
| 32 |
+
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
|
| 33 |
+
metrics:
|
| 34 |
+
- type: accuracy
|
| 35 |
+
value: 92.95087500000001
|
| 36 |
+
- type: ap
|
| 37 |
+
value: 89.92451248271642
|
| 38 |
+
- type: f1
|
| 39 |
+
value: 92.94162732408543
|
| 40 |
+
- task:
|
| 41 |
+
type: Classification
|
| 42 |
+
dataset:
|
| 43 |
+
type: mteb/amazon_reviews_multi
|
| 44 |
+
name: MTEB AmazonReviewsClassification (en)
|
| 45 |
+
config: en
|
| 46 |
+
split: test
|
| 47 |
+
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
| 48 |
+
metrics:
|
| 49 |
+
- type: accuracy
|
| 50 |
+
value: 48.214
|
| 51 |
+
- type: f1
|
| 52 |
+
value: 47.57084372829096
|
| 53 |
+
- task:
|
| 54 |
+
type: Classification
|
| 55 |
+
dataset:
|
| 56 |
+
type: mteb/banking77
|
| 57 |
+
name: MTEB Banking77Classification
|
| 58 |
+
config: default
|
| 59 |
+
split: test
|
| 60 |
+
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
|
| 61 |
+
metrics:
|
| 62 |
+
- type: accuracy
|
| 63 |
+
value: 86.35064935064935
|
| 64 |
+
- type: f1
|
| 65 |
+
value: 86.32782396028989
|
| 66 |
+
- task:
|
| 67 |
+
type: Classification
|
| 68 |
+
dataset:
|
| 69 |
+
type: mteb/emotion
|
| 70 |
+
name: MTEB EmotionClassification
|
| 71 |
+
config: default
|
| 72 |
+
split: test
|
| 73 |
+
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
|
| 74 |
+
metrics:
|
| 75 |
+
- type: accuracy
|
| 76 |
+
value: 51.269999999999996
|
| 77 |
+
- type: f1
|
| 78 |
+
value: 45.9714399031315
|
| 79 |
+
- task:
|
| 80 |
+
type: Classification
|
| 81 |
+
dataset:
|
| 82 |
+
type: mteb/imdb
|
| 83 |
+
name: MTEB ImdbClassification
|
| 84 |
+
config: default
|
| 85 |
+
split: test
|
| 86 |
+
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
|
| 87 |
+
metrics:
|
| 88 |
+
- type: accuracy
|
| 89 |
+
value: 89.7204
|
| 90 |
+
- type: ap
|
| 91 |
+
value: 85.70238397381907
|
| 92 |
+
- type: f1
|
| 93 |
+
value: 89.70961232185473
|
| 94 |
+
- task:
|
| 95 |
+
type: Classification
|
| 96 |
+
dataset:
|
| 97 |
+
type: mteb/mtop_domain
|
| 98 |
+
name: MTEB MTOPDomainClassification (en)
|
| 99 |
+
config: en
|
| 100 |
+
split: test
|
| 101 |
+
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
|
| 102 |
+
metrics:
|
| 103 |
+
- type: accuracy
|
| 104 |
+
value: 93.95120839033288
|
| 105 |
+
- type: f1
|
| 106 |
+
value: 93.70348712248138
|
| 107 |
+
- task:
|
| 108 |
+
type: Classification
|
| 109 |
+
dataset:
|
| 110 |
+
type: mteb/mtop_intent
|
| 111 |
+
name: MTEB MTOPIntentClassification (en)
|
| 112 |
+
config: en
|
| 113 |
+
split: test
|
| 114 |
+
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
|
| 115 |
+
metrics:
|
| 116 |
+
- type: accuracy
|
| 117 |
+
value: 75.25763793889648
|
| 118 |
+
- type: f1
|
| 119 |
+
value: 57.59583082574482
|
| 120 |
+
- task:
|
| 121 |
+
type: Classification
|
| 122 |
+
dataset:
|
| 123 |
+
type: mteb/amazon_massive_intent
|
| 124 |
+
name: MTEB MassiveIntentClassification (en)
|
| 125 |
+
config: en
|
| 126 |
+
split: test
|
| 127 |
+
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
| 128 |
+
metrics:
|
| 129 |
+
- type: accuracy
|
| 130 |
+
value: 75.16476126429052
|
| 131 |
+
- type: f1
|
| 132 |
+
value: 73.29287381030854
|
| 133 |
+
- task:
|
| 134 |
+
type: Classification
|
| 135 |
+
dataset:
|
| 136 |
+
type: mteb/amazon_massive_scenario
|
| 137 |
+
name: MTEB MassiveScenarioClassification (en)
|
| 138 |
+
config: en
|
| 139 |
+
split: test
|
| 140 |
+
revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
| 141 |
+
metrics:
|
| 142 |
+
- type: accuracy
|
| 143 |
+
value: 78.9340954942838
|
| 144 |
+
- type: f1
|
| 145 |
+
value: 79.04036413238218
|
| 146 |
+
- task:
|
| 147 |
+
type: Classification
|
| 148 |
+
dataset:
|
| 149 |
+
type: mteb/toxic_conversations_50k
|
| 150 |
+
name: MTEB ToxicConversationsClassification
|
| 151 |
+
config: default
|
| 152 |
+
split: test
|
| 153 |
+
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
|
| 154 |
+
metrics:
|
| 155 |
+
- type: accuracy
|
| 156 |
+
value: 72.123
|
| 157 |
+
- type: ap
|
| 158 |
+
value: 14.396060207954983
|
| 159 |
+
- type: f1
|
| 160 |
+
value: 55.24344377812756
|
| 161 |
+
- task:
|
| 162 |
+
type: Classification
|
| 163 |
+
dataset:
|
| 164 |
+
type: mteb/tweet_sentiment_extraction
|
| 165 |
+
name: MTEB TweetSentimentExtractionClassification
|
| 166 |
+
config: default
|
| 167 |
+
split: test
|
| 168 |
+
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
|
| 169 |
+
metrics:
|
| 170 |
+
- type: accuracy
|
| 171 |
+
value: 59.67176004527447
|
| 172 |
+
- type: f1
|
| 173 |
+
value: 59.97320225890037
|
| 174 |
---
|
| 175 |
This is the quantized (INT8) ONNX variant of the [bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) embeddings model created with [DeepSparse Optimum](https://github.com/neuralmagic/optimum-deepsparse) for ONNX export/inference pipeline and Neural Magic's [Sparsify](https://github.com/neuralmagic/sparsify) for one-shot quantization.
|
| 176 |
|