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DanielNRU
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pollen-ner-750

PEFT
Safetensors
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  2. adapter_model.safetensors +1 -1
README.md CHANGED
@@ -19,10 +19,10 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [DeepPavlov/rubert-base-cased](https://huggingface.co/DeepPavlov/rubert-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1796
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- - Precision: 0.8007
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- - Recall: 0.8795
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- - F1: 0.8383
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  ## Model description
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@@ -53,14 +53,13 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
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- | No log | 1.0 | 94 | 0.1934 | 0.7879 | 0.8655 | 0.8249 |
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- | No log | 2.0 | 188 | 0.2024 | 0.7739 | 0.8795 | 0.8233 |
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- | No log | 3.0 | 282 | 0.1939 | 0.7774 | 0.8835 | 0.8271 |
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- | No log | 4.0 | 376 | 0.1891 | 0.7878 | 0.8795 | 0.8311 |
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- | No log | 5.0 | 470 | 0.1907 | 0.7843 | 0.8835 | 0.8310 |
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- | 0.3998 | 6.0 | 564 | 0.1796 | 0.8007 | 0.8795 | 0.8383 |
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- | 0.3998 | 7.0 | 658 | 0.1930 | 0.7809 | 0.8876 | 0.8308 |
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- | 0.3998 | 8.0 | 752 | 0.1833 | 0.7939 | 0.8815 | 0.8354 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [DeepPavlov/rubert-base-cased](https://huggingface.co/DeepPavlov/rubert-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1931
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+ - Precision: 0.7953
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+ - Recall: 0.8896
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+ - F1: 0.8398
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
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+ | No log | 1.0 | 94 | 0.1979 | 0.7802 | 0.8695 | 0.8224 |
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+ | No log | 2.0 | 188 | 0.2063 | 0.7583 | 0.8755 | 0.8127 |
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+ | No log | 3.0 | 282 | 0.1991 | 0.7770 | 0.8815 | 0.8260 |
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+ | No log | 4.0 | 376 | 0.1969 | 0.7825 | 0.8815 | 0.8291 |
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+ | No log | 5.0 | 470 | 0.1931 | 0.7953 | 0.8896 | 0.8398 |
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+ | 0.3927 | 6.0 | 564 | 0.1873 | 0.7975 | 0.8855 | 0.8392 |
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+ | 0.3927 | 7.0 | 658 | 0.1950 | 0.7809 | 0.8876 | 0.8308 |
 
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  ### Framework versions
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