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yukta10_finetuning-sentiment-model-3000-samples-finetuned-lora-tweet_eval_irony

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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: 0.6701570680628273
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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 [yukta10/finetuning-sentiment-model-3000-samples](https://huggingface.co/yukta10/finetuning-sentiment-model-3000-samples) 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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@@ -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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  | 0.5602 | None | 0 |
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- | 0.6304 | 0.6678 | 0 |
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- | 0.6398 | 0.6209 | 1 |
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- | 0.6565 | 0.5806 | 2 |
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- | 0.6440 | 0.5570 | 3 |
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- | 0.6618 | 0.5365 | 4 |
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- | 0.6618 | 0.5145 | 5 |
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- | 0.6806 | 0.4947 | 6 |
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- | 0.6702 | 0.4837 | 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: 0.6722513089005235
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  name: accuracy
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  ---
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  This model is a fine-tuned version of [yukta10/finetuning-sentiment-model-3000-samples](https://huggingface.co/yukta10/finetuning-sentiment-model-3000-samples) on the tweet_eval dataset.
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  It achieves the following results on the evaluation set:
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+ - accuracy: 0.6723
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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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+ | 0.6283 | 0.6680 | 0 |
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+ | 0.6461 | 0.6166 | 1 |
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+ | 0.6618 | 0.5835 | 2 |
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+ | 0.6513 | 0.5518 | 3 |
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+ | 0.6597 | 0.5271 | 4 |
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+ | 0.6471 | 0.5118 | 5 |
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+ | 0.6712 | 0.4909 | 6 |
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+ | 0.6723 | 0.4818 | 7 |
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  ### Framework versions
adapter_model.safetensors CHANGED
@@ -1,3 +1,3 @@
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