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End of training

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README.md ADDED
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+ ---
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+ base_model: Anwaarma/Merged-Server-praj
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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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+ model-index:
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+ - name: S02
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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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+ # S02
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+
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+ This model is a fine-tuned version of [Anwaarma/Merged-Server-praj](https://huggingface.co/Anwaarma/Merged-Server-praj) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7888
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+ - Accuracy: 0.31
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+ - F1: 0.4733
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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: 5e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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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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+ - 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 | Accuracy | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | No log | 0.0 | 50 | 0.5805 | 0.6 | 0.5992 |
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+ | No log | 0.01 | 100 | 0.5687 | 0.65 | 0.6505 |
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+ | No log | 0.01 | 150 | 0.5711 | 0.64 | 0.6404 |
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+ | No log | 0.01 | 200 | 0.5643 | 0.67 | 0.6678 |
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+ | No log | 0.02 | 250 | 0.5757 | 0.64 | 0.6393 |
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+ | No log | 0.02 | 300 | 0.5855 | 0.66 | 0.6517 |
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+ | No log | 0.02 | 350 | 0.5529 | 0.63 | 0.6260 |
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+ | No log | 0.03 | 400 | 0.5646 | 0.62 | 0.6105 |
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+ | No log | 0.03 | 450 | 0.5814 | 0.61 | 0.6087 |
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+ | 0.5986 | 0.03 | 500 | 0.5702 | 0.62 | 0.6129 |
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+ | 0.5986 | 0.04 | 550 | 0.5618 | 0.62 | 0.6205 |
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+ | 0.5986 | 0.04 | 600 | 0.5517 | 0.63 | 0.6306 |
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+ | 0.5986 | 0.04 | 650 | 0.5522 | 0.62 | 0.6192 |
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+ | 0.5986 | 0.05 | 700 | 0.5524 | 0.63 | 0.6288 |
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+ | 0.5986 | 0.05 | 750 | 0.5619 | 0.64 | 0.6404 |
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+ | 0.5986 | 0.05 | 800 | 0.5638 | 0.64 | 0.64 |
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+ | 0.5986 | 0.06 | 850 | 0.5481 | 0.66 | 0.6605 |
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+ | 0.5986 | 0.06 | 900 | 0.5562 | 0.64 | 0.64 |
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+ | 0.5986 | 0.06 | 950 | 0.5502 | 0.64 | 0.6354 |
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+ | 0.5834 | 0.07 | 1000 | 0.5970 | 0.68 | 0.6606 |
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+ | 0.5834 | 0.07 | 1050 | 0.5369 | 0.67 | 0.6702 |
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+ | 0.5834 | 0.07 | 1100 | 0.5970 | 0.6 | 0.5966 |
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+ | 0.5834 | 0.08 | 1150 | 0.5770 | 0.62 | 0.6192 |
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+ | 0.5834 | 0.08 | 1200 | 0.5582 | 0.63 | 0.6306 |
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+ | 0.5834 | 0.09 | 1250 | 0.5505 | 0.66 | 0.66 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.0
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+ - Tokenizers 0.15.0
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