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  1. README.md +13 -12
  2. adapter_model.safetensors +1 -1
README.md CHANGED
@@ -18,8 +18,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [nlptown/bert-base-multilingual-uncased-sentiment](https://huggingface.co/nlptown/bert-base-multilingual-uncased-sentiment) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: nan
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- - Accuracy: 0.5
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  ## Model description
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@@ -45,21 +45,22 @@ The following hyperparameters were used during training:
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - num_epochs: 10
 
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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- | 0.0 | 1.0 | 1563 | nan | 0.5 |
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- | 0.0 | 2.0 | 3126 | nan | 0.5 |
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- | 0.0 | 3.0 | 4689 | nan | 0.5 |
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- | 0.0 | 4.0 | 6252 | nan | 0.5 |
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- | 0.0 | 5.0 | 7815 | nan | 0.5 |
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- | 0.0 | 6.0 | 9378 | nan | 0.5 |
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- | 0.0 | 7.0 | 10941 | nan | 0.5 |
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- | 0.0 | 8.0 | 12504 | nan | 0.5 |
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- | 0.0 | 9.0 | 14067 | nan | 0.5 |
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- | 0.0 | 10.0 | 15630 | nan | 0.5 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [nlptown/bert-base-multilingual-uncased-sentiment](https://huggingface.co/nlptown/bert-base-multilingual-uncased-sentiment) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2116
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+ - Accuracy: 0.9224
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  ## Model description
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - num_epochs: 10
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+ - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 0.2559 | 1.0 | 1563 | 0.2355 | 0.9088 |
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+ | 0.2406 | 2.0 | 3126 | 0.2285 | 0.9134 |
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+ | 0.2322 | 3.0 | 4689 | 0.2185 | 0.9173 |
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+ | 0.2291 | 4.0 | 6252 | 0.2174 | 0.9193 |
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+ | 0.2177 | 5.0 | 7815 | 0.2171 | 0.9186 |
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+ | 0.2218 | 6.0 | 9378 | 0.2154 | 0.9202 |
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+ | 0.2116 | 7.0 | 10941 | 0.2127 | 0.9221 |
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+ | 0.2133 | 8.0 | 12504 | 0.2101 | 0.9225 |
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+ | 0.2076 | 9.0 | 14067 | 0.2125 | 0.9221 |
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+ | 0.2029 | 10.0 | 15630 | 0.2116 | 0.9224 |
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  ### Framework versions
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