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gchhablani_bert-base-cased-finetuned-wnli-finetuned-lora-tweet_eval_irony

Text Classification
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Safetensors
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Eval Results
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Finished training.

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  1. README.md +10 -10
  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: 0.6554973821989529
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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 [gchhablani/bert-base-cased-finetuned-wnli](https://huggingface.co/gchhablani/bert-base-cased-finetuned-wnli) on the tweet_eval dataset.
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  It achieves the following results on the evaluation set:
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- - accuracy: 0.6555
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  ## Model description
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@@ -66,14 +66,14 @@ The following hyperparameters were used during training:
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  | accuracy | train_loss | epoch |
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  |:--------:|:----------:|:-----:|
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  | 0.5225 | None | 0 |
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- | 0.5696 | 0.7074 | 0 |
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- | 0.5466 | 0.6701 | 1 |
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- | 0.5832 | 0.6406 | 2 |
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- | 0.6178 | 0.6225 | 3 |
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- | 0.6408 | 0.5966 | 4 |
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- | 0.6178 | 0.5827 | 5 |
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- | 0.6440 | 0.5619 | 6 |
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- | 0.6555 | 0.5582 | 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: 0.6617801047120419
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  name: accuracy
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  ---
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  This model is a fine-tuned version of [gchhablani/bert-base-cased-finetuned-wnli](https://huggingface.co/gchhablani/bert-base-cased-finetuned-wnli) on the tweet_eval dataset.
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  It achieves the following results on the evaluation set:
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+ - accuracy: 0.6618
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  ## Model description
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  | accuracy | train_loss | epoch |
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  |:--------:|:----------:|:-----:|
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  | 0.5225 | None | 0 |
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+ | 0.5801 | 0.7086 | 0 |
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+ | 0.5529 | 0.6679 | 1 |
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+ | 0.6052 | 0.6339 | 2 |
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+ | 0.6440 | 0.6083 | 3 |
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+ | 0.6461 | 0.5908 | 4 |
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+ | 0.6293 | 0.5716 | 5 |
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+ | 0.6534 | 0.5522 | 6 |
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+ | 0.6618 | 0.5513 | 7 |
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  ### Framework versions
adapter_model.safetensors CHANGED
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