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manipulative-score-model

Text Classification
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xlm-roberta
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  1. README.md +91 -0
  2. final/model.safetensors +1 -1
  3. final/training_args.bin +1 -1
  4. model.safetensors +1 -1
  5. runs/Sep14_18-58-42_fs-cai-004/events.out.tfevents.1757876326.fs-cai-004.1849626.0 +2 -2
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: intfloat/multilingual-e5-base
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - precision
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+ - recall
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+ - accuracy
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+ model-index:
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+ - name: manipulative-score-model
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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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+ # manipulative-score-model
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+
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+ This model is a fine-tuned version of [intfloat/multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1483
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+ - Precision: 0.7768
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+ - Recall: 0.7324
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+ - F1 Macro: 0.7468
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+ - Accuracy: 0.7962
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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: 3e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 128
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+ - seed: 0
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+ - distributed_type: multi-GPU
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+ - num_devices: 8
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+ - total_train_batch_size: 256
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+ - total_eval_batch_size: 1024
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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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+ - lr_scheduler_warmup_steps: 60
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+ - num_epochs: 20
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 Macro | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:--------:|
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+ | No log | 0 | 0 | 0.2718 | 0.3406 | 0.5 | 0.4052 | 0.6813 |
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+ | No log | 1.0 | 15 | 0.2254 | 0.5393 | 0.5041 | 0.4294 | 0.6764 |
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+ | No log | 2.0 | 30 | 0.2176 | 0.6641 | 0.5041 | 0.4161 | 0.6828 |
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+ | No log | 3.0 | 45 | 0.2020 | 0.7742 | 0.5255 | 0.4603 | 0.6959 |
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+ | No log | 4.0 | 60 | 0.1851 | 0.7603 | 0.5817 | 0.5649 | 0.7255 |
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+ | No log | 5.0 | 75 | 0.1731 | 0.7466 | 0.6506 | 0.6624 | 0.7550 |
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+ | No log | 6.0 | 90 | 0.1654 | 0.7556 | 0.6772 | 0.6924 | 0.7683 |
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+ | 0.203 | 7.0 | 105 | 0.1606 | 0.7602 | 0.6873 | 0.7032 | 0.7737 |
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+ | 0.203 | 8.0 | 120 | 0.1574 | 0.7701 | 0.6920 | 0.7089 | 0.7789 |
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+ | 0.203 | 9.0 | 135 | 0.1557 | 0.7798 | 0.6845 | 0.7017 | 0.7787 |
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+ | 0.203 | 10.0 | 150 | 0.1548 | 0.7858 | 0.6824 | 0.6998 | 0.7794 |
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+ | 0.203 | 11.0 | 165 | 0.1525 | 0.7812 | 0.7002 | 0.7182 | 0.7859 |
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+ | 0.203 | 12.0 | 180 | 0.1517 | 0.7862 | 0.7023 | 0.7208 | 0.7883 |
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+ | 0.203 | 13.0 | 195 | 0.1515 | 0.7895 | 0.6991 | 0.7178 | 0.7880 |
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+ | 0.1516 | 14.0 | 210 | 0.1502 | 0.7724 | 0.7295 | 0.7435 | 0.7932 |
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+ | 0.1516 | 15.0 | 225 | 0.1495 | 0.7751 | 0.7293 | 0.7440 | 0.7944 |
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+ | 0.1516 | 16.0 | 240 | 0.1489 | 0.7763 | 0.7277 | 0.7429 | 0.7944 |
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+ | 0.1516 | 17.0 | 255 | 0.1485 | 0.7781 | 0.7230 | 0.7391 | 0.7935 |
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+ | 0.1516 | 18.0 | 270 | 0.1483 | 0.7781 | 0.7275 | 0.7430 | 0.7951 |
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+ | 0.1516 | 19.0 | 285 | 0.1482 | 0.7787 | 0.7258 | 0.7417 | 0.7948 |
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+ | 0.1421 | 20.0 | 300 | 0.1483 | 0.7768 | 0.7324 | 0.7468 | 0.7962 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.56.1
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+ - Pytorch 2.6.0a0+ecf3bae40a.nv25.01
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+ - Datasets 4.0.0
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+ - Tokenizers 0.22.0
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