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oferweintraub_bert-base-finance-sentiment-noisy-search-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
@@ -23,7 +23,7 @@ model-index:
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  args: irony
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  metrics:
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  - type: accuracy
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- value: 0.6732984293193718
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  name: accuracy
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  ---
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@@ -34,7 +34,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [oferweintraub/bert-base-finance-sentiment-noisy-search](https://huggingface.co/oferweintraub/bert-base-finance-sentiment-noisy-search) on the tweet_eval dataset.
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  It achieves the following results on the evaluation set:
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- - accuracy: 0.6733
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  ## Model description
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  | accuracy | train_loss | epoch |
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  |:--------:|:----------:|:-----:|
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- | 0.5602 | None | 0 |
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- | 0.5780 | 0.6957 | 0 |
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- | 0.5822 | 0.6821 | 1 |
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- | 0.6094 | 0.6497 | 2 |
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- | 0.6293 | 0.6274 | 3 |
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- | 0.6618 | 0.6080 | 4 |
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- | 0.6576 | 0.5930 | 5 |
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- | 0.6660 | 0.5825 | 6 |
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- | 0.6733 | 0.5663 | 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: 0.6575916230366492
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  name: accuracy
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  ---
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  This model is a fine-tuned version of [oferweintraub/bert-base-finance-sentiment-noisy-search](https://huggingface.co/oferweintraub/bert-base-finance-sentiment-noisy-search) on the tweet_eval dataset.
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  It achieves the following results on the evaluation set:
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+ - accuracy: 0.6576
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  ## Model description
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  | accuracy | train_loss | epoch |
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  |:--------:|:----------:|:-----:|
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+ | 0.5162 | None | 0 |
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+ | 0.5738 | 0.6967 | 0 |
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+ | 0.5435 | 0.6857 | 1 |
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+ | 0.5958 | 0.6657 | 2 |
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+ | 0.6325 | 0.6477 | 3 |
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+ | 0.6461 | 0.6235 | 4 |
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+ | 0.6534 | 0.6148 | 5 |
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+ | 0.6398 | 0.6032 | 6 |
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+ | 0.6576 | 0.5911 | 7 |
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  ### Framework versions
adapter_model.safetensors CHANGED
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