diff --git "a/README.md" "b/README.md" --- "a/README.md" +++ "b/README.md" @@ -41,25 +41,25 @@ model-index: type: test_cls metrics: - type: accuracy - value: 0.5661078569985861 + value: 0.5674139904396418 name: Accuracy - type: accuracy_threshold - value: -1.8359375 + value: -1.8671875 name: Accuracy Threshold - type: f1 - value: 0.6381983914209115 + value: 0.6387997297069009 name: F1 - type: f1_threshold - value: -3.0 + value: -3.0625 name: F1 Threshold - type: precision - value: 0.49571026371466176 + value: 0.49197417424254747 name: Precision - type: recall - value: 0.895644583571622 + value: 0.9105439003100262 name: Recall - type: average_precision - value: 0.5123490100661972 + value: 0.5139387312514831 name: Average Precision - task: type: cross-encoder-reranking @@ -69,13 +69,13 @@ model-index: type: NanoQuoraRetrieval_R25 metrics: - type: map - value: 0.2548 + value: 0.265 name: Map - type: mrr@1 - value: 0.12 + value: 0.16 name: Mrr@1 - type: ndcg@1 - value: 0.12 + value: 0.16 name: Ndcg@1 - task: type: cross-encoder-reranking @@ -85,13 +85,13 @@ model-index: type: NanoMSMARCO_R25 metrics: - type: map - value: 0.187 + value: 0.1716 name: Map - type: mrr@1 - value: 0.06 + value: 0.04 name: Mrr@1 - type: ndcg@1 - value: 0.06 + value: 0.04 name: Ndcg@1 - task: type: cross-encoder-reranking @@ -101,7 +101,7 @@ model-index: type: NanoNQ_R25 metrics: - type: map - value: 0.1356 + value: 0.1513 name: Map - type: mrr@1 value: 0.04 @@ -117,13 +117,13 @@ model-index: type: NanoBEIR_R25_mean metrics: - type: map - value: 0.1925 + value: 0.196 name: Map - type: mrr@1 - value: 0.0733 + value: 0.08 name: Mrr@1 - type: ndcg@1 - value: 0.0733 + value: 0.08 name: Ndcg@1 --- @@ -227,13 +227,13 @@ You can finetune this model on your own dataset. | Metric | Value | |:----------------------|:-----------| -| accuracy | 0.5661 | -| accuracy_threshold | -1.8359 | -| f1 | 0.6382 | -| f1_threshold | -3.0 | -| precision | 0.4957 | -| recall | 0.8956 | -| **average_precision** | **0.5123** | +| accuracy | 0.5674 | +| accuracy_threshold | -1.8672 | +| f1 | 0.6388 | +| f1_threshold | -3.0625 | +| precision | 0.492 | +| recall | 0.9105 | +| **average_precision** | **0.5139** | #### Cross Encoder Reranking @@ -248,9 +248,9 @@ You can finetune this model on your own dataset. | Metric | NanoQuoraRetrieval_R25 | NanoMSMARCO_R25 | NanoNQ_R25 | |:-----------|:-----------------------|:---------------------|:---------------------| -| map | 0.2548 (-0.5756) | 0.1870 (-0.3007) | 0.1356 (-0.2844) | -| mrr@1 | 0.1200 (-0.6800) | 0.0600 (-0.2800) | 0.0400 (-0.2000) | -| **ndcg@1** | **0.1200 (-0.6800)** | **0.0600 (-0.2800)** | **0.0400 (-0.2000)** | +| map | 0.2650 (-0.5654) | 0.1716 (-0.3162) | 0.1513 (-0.2687) | +| mrr@1 | 0.1600 (-0.6400) | 0.0400 (-0.3000) | 0.0400 (-0.2000) | +| **ndcg@1** | **0.1600 (-0.6400)** | **0.0400 (-0.3000)** | **0.0400 (-0.2000)** | #### Cross Encoder Nano BEIR @@ -271,9 +271,9 @@ You can finetune this model on your own dataset. | Metric | Value | |:-----------|:---------------------| -| map | 0.1925 (-0.3869) | -| mrr@1 | 0.0733 (-0.3867) | -| **ndcg@1** | **0.0733 (-0.3867)** | +| map | 0.1960 (-0.3834) | +| mrr@1 | 0.0800 (-0.3800) | +| **ndcg@1** | **0.0800 (-0.3800)** |