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--- |
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library_name: peft |
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base_model: cardiffnlp/twitter-roberta-base-sentiment-latest |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: fine_tuned_model |
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results: [] |
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license: apache-2.0 |
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datasets: |
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- mteb/amazon_reviews_multi |
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language: |
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- en |
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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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# fine_tuned_model |
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This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) on [mteb/amazon_reviews_multi](https://huggingface.co/datasets/mteb/amazon_reviews_multi). |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4604 |
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- Accuracy: 0.81 |
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- F1 Macro: 0.7564 |
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- Precision Macro: 0.7654 |
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- Recall Macro: 0.7533 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:---------------:|:------------:| |
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| 0.5451 | 1.0 | 5000 | 0.5156 | 0.783 | 0.7111 | 0.7280 | 0.7110 | |
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| 0.4961 | 2.0 | 10000 | 0.4619 | 0.809 | 0.7591 | 0.7647 | 0.7567 | |
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| 0.498 | 3.0 | 15000 | 0.4604 | 0.81 | 0.7564 | 0.7654 | 0.7533 | |
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### Framework versions |
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- PEFT 0.14.0 |
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- Transformers 4.48.3 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.0 |
