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trainRanker_test_test

Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
Inference Endpoints
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  1. README.md +13 -14
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  ---
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- license: mit
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- base_model: microsoft/Multilingual-MiniLM-L12-H384
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  tags:
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  - generated_from_trainer
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  model-index:
@@ -13,9 +12,9 @@ should probably proofread and complete it, then remove this comment. -->
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  # trainRanker_test_test
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- This model is a fine-tuned version of [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2915
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  ## Model description
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@@ -48,16 +47,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 0.4046 | 0.16 | 200 | 0.3609 |
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- | 0.3704 | 0.32 | 400 | 0.3112 |
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- | 0.3404 | 0.48 | 600 | 0.3139 |
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- | 0.3208 | 0.64 | 800 | 0.2955 |
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- | 0.3139 | 0.8 | 1000 | 0.2943 |
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- | 0.3061 | 0.96 | 1200 | 0.2933 |
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- | 0.2857 | 1.12 | 1400 | 0.2915 |
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- | 0.3086 | 1.28 | 1600 | 0.2915 |
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- | 0.283 | 1.44 | 1800 | 0.2915 |
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- | 0.2855 | 1.6 | 2000 | 0.2915 |
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  ### Framework versions
 
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  ---
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+ base_model: nreimers/mMiniLMv2-L6-H384-distilled-from-XLMR-Large
 
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  tags:
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  - generated_from_trainer
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  model-index:
 
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  # trainRanker_test_test
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+ This model is a fine-tuned version of [nreimers/mMiniLMv2-L6-H384-distilled-from-XLMR-Large](https://huggingface.co/nreimers/mMiniLMv2-L6-H384-distilled-from-XLMR-Large) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4322
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.6929 | 0.16 | 200 | 0.6925 |
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+ | 0.6907 | 0.32 | 400 | 0.5492 |
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+ | 0.4975 | 0.48 | 600 | 0.4721 |
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+ | 0.4584 | 0.64 | 800 | 0.4444 |
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+ | 0.4596 | 0.8 | 1000 | 0.4309 |
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+ | 0.4431 | 0.96 | 1200 | 0.4338 |
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+ | 0.4233 | 1.12 | 1400 | 0.4322 |
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+ | 0.4451 | 1.28 | 1600 | 0.4322 |
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+ | 0.4346 | 1.44 | 1800 | 0.4322 |
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+ | 0.4239 | 1.6 | 2000 | 0.4322 |
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  ### Framework versions