hilco commited on
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Finished training.

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README.md ADDED
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+ ---
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+ library_name: peft
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+ tags:
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+ - parquet
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+ - text-classification
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+ datasets:
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+ - tweet_eval
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+ metrics:
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+ - accuracy
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+ base_model: mrm8488/electricidad-base-finetuned-pawsx-es
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+ model-index:
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+ - name: mrm8488_electricidad-base-finetuned-pawsx-es-finetuned-lora-tweet_eval_irony
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+ results:
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+ - task:
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+ type: text-classification
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+ name: Text Classification
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+ dataset:
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+ name: tweet_eval
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+ type: tweet_eval
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+ config: irony
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+ split: validation
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+ args: irony
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+ metrics:
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+ - type: accuracy
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+ value: 0.5947643979057592
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+ name: accuracy
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # mrm8488_electricidad-base-finetuned-pawsx-es-finetuned-lora-tweet_eval_irony
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+
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+ This model is a fine-tuned version of [mrm8488/electricidad-base-finetuned-pawsx-es](https://huggingface.co/mrm8488/electricidad-base-finetuned-pawsx-es) on the tweet_eval dataset.
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+ It achieves the following results on the evaluation set:
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+ - accuracy: 0.5948
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0005
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 8
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+
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+ ### Training results
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+
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+ | accuracy | train_loss | epoch |
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+ |:--------:|:----------:|:-----:|
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+ | 0.4974 | None | 0 |
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+ | 0.5497 | 0.7063 | 0 |
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+ | 0.5466 | 0.6915 | 1 |
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+ | 0.5707 | 0.6660 | 2 |
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+ | 0.5864 | 0.6439 | 3 |
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+ | 0.5728 | 0.6380 | 4 |
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+ | 0.5717 | 0.6324 | 5 |
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+ | 0.5874 | 0.6160 | 6 |
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+ | 0.5948 | 0.6181 | 7 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.8.2
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+ - Transformers 4.37.2
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+ - Pytorch 2.2.0
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.2
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