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--- |
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base_model: google-bert/bert-base-uncased |
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library_name: peft |
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license: apache-2.0 |
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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: bert-sst2-sentiment-lora |
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results: [] |
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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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# bert-sst2-sentiment-lora |
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This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2664 |
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- Accuracy: 0.9094 |
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- F1: 0.9123 |
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- Precision: 0.8993 |
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- Recall: 0.9257 |
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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: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 64 |
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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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- lr_scheduler_warmup_steps: 500 |
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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 | Precision | Recall | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.3043 | 1.0 | 4210 | 0.2483 | 0.9128 | 0.9148 | 0.9107 | 0.9189 | |
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| 0.2494 | 2.0 | 8420 | 0.2577 | 0.9083 | 0.9109 | 0.9009 | 0.9212 | |
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| 0.1861 | 3.0 | 12630 | 0.2664 | 0.9094 | 0.9123 | 0.8993 | 0.9257 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
