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jslai//content/sample_data/best_models//MBERT_uncased_SymmetricCrossEntropy_lora

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README.md ADDED
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+ ---
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+ library_name: peft
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+ license: apache-2.0
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+ base_model: google-bert/bert-base-multilingual-uncased
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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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+ - f1
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+ - precision
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+ - recall
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+ model-index:
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+ - name: MBERT_uncased_SymmetricCrossEntropy_lora
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+ results: []
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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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+ # MBERT_uncased_SymmetricCrossEntropy_lora
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+
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+ This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7435
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+ - Accuracy: 0.711
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+ - F1: 0.8311
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+ - Precision: 0.7204
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+ - Recall: 0.9820
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+ - Roc Auc: 0.4910
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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: 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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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 32
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+ - optimizer: Use 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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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 3
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Roc Auc |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------:|
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+ | No log | 0.992 | 31 | 0.7593 | 0.622 | 0.7638 | 0.6975 | 0.8439 | 0.4419 |
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+ | No log | 1.984 | 62 | 0.7473 | 0.702 | 0.8249 | 0.7178 | 0.9696 | 0.4848 |
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+ | No log | 2.976 | 93 | 0.7435 | 0.711 | 0.8311 | 0.7204 | 0.9820 | 0.4910 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.13.3.dev0
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+ - Transformers 4.46.2
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+ - Pytorch 2.5.0+cu121
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+ - Datasets 3.1.0
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+ - Tokenizers 0.20.3
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