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jb2k_bert-base-multilingual-cased-language-detection-finetuned-lora-tweet_eval_irony

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Eval Results
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Finished training.

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  1. README.md +11 -11
  2. adapter_model.safetensors +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  args: irony
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  metrics:
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  - type: accuracy
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- value: 0.5979057591623037
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  name: accuracy
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  ---
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@@ -33,7 +33,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [jb2k/bert-base-multilingual-cased-language-detection](https://huggingface.co/jb2k/bert-base-multilingual-cased-language-detection) on the tweet_eval dataset.
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  It achieves the following results on the evaluation set:
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- - accuracy: 0.5979
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  ## Model description
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  | accuracy | train_loss | epoch |
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  |:--------:|:----------:|:-----:|
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- | 0.4775 | None | 0 |
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- | 0.5393 | 0.6881 | 0 |
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- | 0.5707 | 0.6721 | 1 |
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- | 0.5874 | 0.6547 | 2 |
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- | 0.5853 | 0.6313 | 3 |
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- | 0.5780 | 0.6249 | 4 |
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- | 0.5738 | 0.6182 | 5 |
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- | 0.5979 | 0.6085 | 6 |
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- | 0.5979 | 0.6083 | 7 |
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  ### Framework versions
 
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  args: irony
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  metrics:
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  - type: accuracy
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+ value: 0.5905759162303665
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  name: accuracy
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  ---
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  This model is a fine-tuned version of [jb2k/bert-base-multilingual-cased-language-detection](https://huggingface.co/jb2k/bert-base-multilingual-cased-language-detection) on the tweet_eval dataset.
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  It achieves the following results on the evaluation set:
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+ - accuracy: 0.5906
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  ## Model description
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  | accuracy | train_loss | epoch |
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  |:--------:|:----------:|:-----:|
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+ | 0.4806 | None | 0 |
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+ | 0.5476 | 0.6896 | 0 |
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+ | 0.5654 | 0.6710 | 1 |
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+ | 0.5738 | 0.6549 | 2 |
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+ | 0.5770 | 0.6416 | 3 |
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+ | 0.5801 | 0.6325 | 4 |
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+ | 0.5853 | 0.6288 | 5 |
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+ | 0.5853 | 0.6242 | 6 |
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+ | 0.5906 | 0.6154 | 7 |
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  ### Framework versions
adapter_model.safetensors CHANGED
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