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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: 0.680628272251309
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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 [anirudh21/bert-base-uncased-finetuned-qnli](https://huggingface.co/anirudh21/bert-base-uncased-finetuned-qnli) on the tweet_eval dataset.
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  It achieves the following results on the evaluation set:
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- - accuracy: 0.6806
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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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  | 0.5026 | None | 0 |
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- | 0.5581 | 0.7071 | 0 |
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- | 0.6272 | 0.6588 | 1 |
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- | 0.6586 | 0.6087 | 2 |
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- | 0.6607 | 0.5812 | 3 |
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- | 0.6628 | 0.5597 | 4 |
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- | 0.6545 | 0.5463 | 5 |
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- | 0.6670 | 0.5410 | 6 |
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- | 0.6806 | 0.5387 | 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: 0.6701570680628273
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  name: accuracy
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  ---
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  This model is a fine-tuned version of [anirudh21/bert-base-uncased-finetuned-qnli](https://huggingface.co/anirudh21/bert-base-uncased-finetuned-qnli) on the tweet_eval dataset.
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  It achieves the following results on the evaluation set:
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+ - accuracy: 0.6702
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  ## Model description
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  | accuracy | train_loss | epoch |
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  |:--------:|:----------:|:-----:|
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  | 0.5026 | None | 0 |
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+ | 0.5623 | 0.7046 | 0 |
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+ | 0.6052 | 0.6689 | 1 |
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+ | 0.6272 | 0.6211 | 2 |
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+ | 0.6681 | 0.5951 | 3 |
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+ | 0.6482 | 0.5692 | 4 |
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+ | 0.6492 | 0.5597 | 5 |
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+ | 0.6691 | 0.5490 | 6 |
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+ | 0.6702 | 0.5413 | 7 |
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  ### Framework versions
adapter_model.safetensors CHANGED
@@ -1,3 +1,3 @@
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  size 160400
 
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