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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: sheepy928/default
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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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+ - recall
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+ - precision
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+ model-index:
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+ - name: FT_3
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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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+ # FT_3
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+
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+ This model is a fine-tuned version of [sheepy928/default](https://huggingface.co/sheepy928/default) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7570
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+ - Accuracy: 0.7393
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+ - F1: 0.6292
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+ - Recall: 0.7393
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+ - Precision: 0.7147
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+ - Combined Score: 0.7056
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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: 8
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - distributed_type: multi-GPU
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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: 10000
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+ - num_epochs: 30
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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 | Recall | Precision | Combined Score |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|:--------------:|
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+ | 0.6785 | 1.6 | 300 | 0.7930 | 0.7387 | 0.6276 | 0.7387 | 0.5456 | 0.6627 |
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+ | 0.5583 | 3.19 | 600 | 0.6910 | 0.7613 | 0.7316 | 0.7613 | 0.7072 | 0.7404 |
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+ | 0.7857 | 4.79 | 900 | 0.6515 | 0.7387 | 0.6276 | 0.7387 | 0.5456 | 0.6627 |
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+ | 0.6309 | 6.38 | 1200 | 0.5592 | 0.848 | 0.8270 | 0.848 | 0.8382 | 0.8403 |
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+ | 0.2216 | 7.98 | 1500 | 0.5708 | 0.8773 | 0.8432 | 0.8773 | 0.8496 | 0.8619 |
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+ | 0.3214 | 9.57 | 1800 | 0.4550 | 0.896 | 0.8584 | 0.896 | 0.8776 | 0.8820 |
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+ | 0.7521 | 11.17 | 2100 | 0.3819 | 0.884 | 0.8423 | 0.884 | 0.8059 | 0.8541 |
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+ | 0.5048 | 12.77 | 2400 | 0.6582 | 0.7387 | 0.6276 | 0.7387 | 0.5456 | 0.6627 |
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+ | 0.6435 | 14.36 | 2700 | 0.5365 | 0.8467 | 0.8092 | 0.8467 | 0.7798 | 0.8206 |
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+ | 0.9304 | 15.96 | 3000 | 0.7577 | 0.7387 | 0.6289 | 0.7387 | 0.6302 | 0.6841 |
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+ | 0.7902 | 17.55 | 3300 | 0.7684 | 0.7387 | 0.6289 | 0.7387 | 0.6302 | 0.6841 |
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+ | 0.6364 | 19.15 | 3600 | 0.7638 | 0.7387 | 0.6289 | 0.7387 | 0.6302 | 0.6841 |
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+ | 0.6738 | 20.74 | 3900 | 0.7769 | 0.7393 | 0.6292 | 0.7393 | 0.7147 | 0.7056 |
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+ | 0.8142 | 22.34 | 4200 | 0.7443 | 0.7393 | 0.6292 | 0.7393 | 0.7147 | 0.7056 |
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+ | 0.8184 | 23.94 | 4500 | 0.7635 | 0.7393 | 0.6292 | 0.7393 | 0.7147 | 0.7056 |
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+ | 0.7562 | 25.53 | 4800 | 0.7467 | 0.7393 | 0.6292 | 0.7393 | 0.7147 | 0.7056 |
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+ | 0.5699 | 27.13 | 5100 | 0.7867 | 0.7393 | 0.6292 | 0.7393 | 0.7147 | 0.7056 |
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+ | 0.761 | 28.72 | 5400 | 0.7570 | 0.7393 | 0.6292 | 0.7393 | 0.7147 | 0.7056 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.34.1
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+ - Pytorch 2.1.0
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+ - Datasets 2.14.5
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+ - Tokenizers 0.14.1
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