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AlekseyKorshuk
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twscrape-prepared-regression-Linq-Embed-Mistral-scorer

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Safetensors
mistral
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text-generation-inference
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  1. README.md +18 -18
  2. model-00003-of-00003.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -16,12 +16,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [Linq-AI-Research/Linq-Embed-Mistral](https://huggingface.co/Linq-AI-Research/Linq-Embed-Mistral) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 9.7099
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- - Mse: 9.7098
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- - Target 0 Mse: 18.5035
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- - Target 1 Mse: 9.9817
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- - Target 2 Mse: 5.2868
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- - Target 3 Mse: 5.0672
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  ## Model description
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@@ -55,18 +55,18 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Mse | Target 0 Mse | Target 1 Mse | Target 2 Mse | Target 3 Mse |
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- |:-------------:|:-----:|:----:|:---------------:|:-------:|:------------:|:------------:|:------------:|:------------:|
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- | 16.8047 | 1.0 | 280 | 16.4555 | 16.4594 | 27.7680 | 15.5051 | 11.1613 | 11.4033 |
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- | 11.1602 | 2.0 | 560 | 13.1732 | 13.1774 | 23.3179 | 13.1760 | 8.2887 | 7.9268 |
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- | 12.6055 | 3.0 | 840 | 11.8043 | 11.8031 | 21.3693 | 11.9728 | 7.0819 | 6.7884 |
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- | 11.1562 | 4.0 | 1120 | 10.9693 | 10.9669 | 20.2088 | 11.1752 | 6.3655 | 6.1181 |
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- | 8.6172 | 5.0 | 1400 | 10.4258 | 10.4250 | 19.4563 | 10.6673 | 5.9042 | 5.6723 |
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- | 10.1992 | 6.0 | 1680 | 10.0752 | 10.0751 | 18.9940 | 10.3359 | 5.5939 | 5.3767 |
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- | 7.875 | 7.0 | 1960 | 9.8701 | 9.8630 | 18.7038 | 10.1268 | 5.4208 | 5.2006 |
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- | 8.0508 | 8.0 | 2240 | 9.7511 | 9.7564 | 18.5671 | 10.0269 | 5.3200 | 5.1115 |
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- | 8.0195 | 9.0 | 2520 | 9.7144 | 9.7161 | 18.5102 | 9.9874 | 5.2931 | 5.0737 |
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- | 11.4102 | 10.0 | 2800 | 9.7099 | 9.7098 | 18.5035 | 9.9817 | 5.2868 | 5.0672 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [Linq-AI-Research/Linq-Embed-Mistral](https://huggingface.co/Linq-AI-Research/Linq-Embed-Mistral) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 12.6464
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+ - Mse: 12.6428
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+ - Target 0 Mse: 37.8821
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+ - Target 1 Mse: 8.8989
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+ - Target 2 Mse: 2.5619
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+ - Target 3 Mse: 1.2285
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Mse | Target 0 Mse | Target 1 Mse | Target 2 Mse | Target 3 Mse |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------------:|:------------:|:------------:|:------------:|
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+ | 428.5 | 1.0 | 280 | 347.7662 | 347.8059 | 633.5776 | 263.5729 | 370.2541 | 123.8188 |
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+ | 9.9395 | 2.0 | 560 | 20.6962 | 20.7335 | 42.0764 | 18.6294 | 16.8553 | 5.3730 |
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+ | 11.7539 | 3.0 | 840 | 14.0448 | 14.0469 | 37.0272 | 10.4259 | 5.5888 | 3.1457 |
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+ | 12.293 | 4.0 | 1120 | 13.0462 | 13.0442 | 36.9399 | 8.8813 | 4.1221 | 2.2336 |
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+ | 7.3027 | 5.0 | 1400 | 12.8216 | 12.8139 | 37.2984 | 8.7870 | 3.4468 | 1.7233 |
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+ | 12.8594 | 6.0 | 1680 | 12.7524 | 12.7500 | 37.7420 | 8.7288 | 3.0093 | 1.5198 |
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+ | 6.7754 | 7.0 | 1960 | 12.7292 | 12.7237 | 37.9368 | 8.8719 | 2.7380 | 1.3482 |
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+ | 9.9688 | 8.0 | 2240 | 12.6771 | 12.6815 | 37.9204 | 8.9231 | 2.6111 | 1.2715 |
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+ | 11.9023 | 9.0 | 2520 | 12.6444 | 12.6388 | 37.8705 | 8.8944 | 2.5619 | 1.2285 |
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+ | 19.6836 | 10.0 | 2800 | 12.6464 | 12.6428 | 37.8821 | 8.8989 | 2.5619 | 1.2285 |
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  ### Framework versions
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