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model2vecdk-stem

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@@ -101,15 +101,15 @@ The model can be used as a retriever and it achieved the following performance o
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  The model was also evaluated using the [Scandinavian Embedding Benchmark](https://kennethenevoldsen.github.io/scandinavian-embedding-benchmark/) and achieved the following performance:
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- | Rank | Model | Average Score | Average Rank | Angry Tweets | Bornholm Parallel | DKHate | Da Political Comments | DanFEVER | LCC | Language Identification | Massive Intent | Massive Scenario | ScaLA | TV2Nord Retrieval | Twitterhjerne |
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- |------|--------------------------------|----------------|--------------|--------------|--------------------|--------|------------------------|----------|-------|---------------------------|----------------|------------------|--------|---------------------|----------------|
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- | 1 | TTC-L2V-supervised-2 | 0.68 | 4.75 | 67.09 | 54.59 | 69.00 | 45.84 | 38.31 | 73.67 | 88.61 | 74.80 | 78.35 | 53.04 | 92.79 | 85.02 |
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- | 2 | multilingual-e5-large-instruct | 0.66 | 7.75 | 64.57 | 55.02 | 67.14 | 45.33 | 39.52 | 70.60 | 82.48 | 71.89 | 77.51 | 50.18 | 93.69 | 77.23 |
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- | 3 | text-embedding-3-large | 0.64 | 8.92 | 57.80 | 43.34 | 70.21 | 43.41 | 39.61 | 58.07 | 79.74 | 69.27 | 75.92 | 50.69 | 95.20 | 81.08 |
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- | 42 | dfm-encoder-small-v1 (SimCSE) | 0.42 | 33.54 | 51.92 | 40.82 | 60.00 | 35.25 | 16.99 | 58.53 | 50.50 | 47.92 | 52.95 | 51.36 | 22.28 | 20.02 |
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- | 43 | **model2vecdk-stem** | 0.42 | 36.62 | 48.19 | 7.83 | 59.73 | 32.40 | 26.04 | 47.67 | 63.97 | 51.23 | 60.87 | 50.18 | 55.47 | 20.19 |
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- | 44 | xlm-roberta-large | 0.40 | 35.92 | 51.74 | 4.34 | 60.21 | 31.85 | 10.62 | 48.73 | 81.29 | 47.26 | 49.55 | 60.29 | 6.11 | 20.39 |
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  The model was also evaluated using the [Scandinavian Embedding Benchmark](https://kennethenevoldsen.github.io/scandinavian-embedding-benchmark/) and achieved the following performance:
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+ | Rank | Model | Average Score | Average Rank | Angry Tweets | Bornholm Parallel | DKHate | Da Political Comments | DanFEVER | LCC | Language Identification | Massive Intent | Massive Scenario | ScaLA | TV2Nord Retrieval | Twitterhjerne |
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+ |------|-------|---------------|--------------|--------------|-------------------|--------|----------------------|----------|-----|------------------------|----------------|------------------|-------|-------------------|---------------|
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+ | 1 | TTC-L2V-supervised-2 | 0.68 | 4.75 | 67.09 | 54.59 | 69.00 | 45.84 | 38.31 | 73.67 | 88.61 | 74.80 | 78.35 | 53.04 | 92.79 | 85.02 |
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+ | 2 | multilingual-e5-large-instruct | 0.66 | 7.67 | 64.57 | 55.02 | 67.14 | 45.33 | 39.52 | 70.60 | 82.48 | 71.89 | 77.51 | 50.18 | 93.69 | 77.23 |
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+ | 3 | text-embedding-3-large | 0.64 | 8.92 | 57.80 | 43.34 | 70.21 | 43.41 | 39.61 | 58.07 | 79.74 | 69.27 | 75.92 | 50.69 | 95.20 | 81.08 |
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+ | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
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+ | 42 | dfm-encoder-small-v1 (SimCSE) | 0.42 | 33.62 | 51.92 | 40.82 | 60.00 | 35.25 | 16.99 | 58.53 | 50.50 | 47.92 | 52.95 | 51.36 | 22.28 | 20.02 |
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+ | 43 | **NEW: model2vecdk-stem** | **0.42** | **37.67** | **46.18** | **9.17** | **60.76** | **29.86** | **27.69** | **43.93** | **61.55** | **48.78** | **55.90** | **50.12** | **57.34** | **25.56** |
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+ | 44 | xlm-roberta-large | 0.40 | 36.00 | 51.74 | 4.34 | 60.21 | 31.85 | 10.62 | 48.73 | 81.29 | 47.26 | 49.55 | 60.29 | 6.11 | 20.39 |
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