End of training
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README.md
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This model is a fine-tuned version of [princeton-nlp/sup-simcse-bert-base-uncased](https://huggingface.co/princeton-nlp/sup-simcse-bert-base-uncased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Precision: 0.
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- Recall: 0.
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- F1: 0.
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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 | 306 | 0.
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| 0.
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| 0.
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### Framework versions
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This model is a fine-tuned version of [princeton-nlp/sup-simcse-bert-base-uncased](https://huggingface.co/princeton-nlp/sup-simcse-bert-base-uncased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1133
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- Precision: 0.5071
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- Recall: 0.6100
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- F1: 0.5538
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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 | 306 | 0.0824 | 0.4993 | 0.5304 | 0.5144 |
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| 0.0847 | 2.0 | 612 | 0.0947 | 0.4961 | 0.5881 | 0.5382 |
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| 0.0847 | 3.0 | 918 | 0.1133 | 0.5071 | 0.6100 | 0.5538 |
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### Framework versions
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model.safetensors
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