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S02-PC

Text Classification
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  1. README.md +97 -0
  2. runs/Dec24_16-55-07_86f59ffbd25a/events.out.tfevents.1703436911.86f59ffbd25a.1423.162 +2 -2
  3. runs/Dec24_16-55-07_86f59ffbd25a/events.out.tfevents.1703436911.86f59ffbd25a.1423.163 +2 -2
  4. runs/Dec24_16-55-07_86f59ffbd25a/events.out.tfevents.1703436958.86f59ffbd25a.1423.164 +3 -0
  5. runs/Dec24_16-55-07_86f59ffbd25a/events.out.tfevents.1703436958.86f59ffbd25a.1423.165 +3 -0
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-PC
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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-PC
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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: 0.5986
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+ - Accuracy: 0.78
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+ - F1: 0.8764
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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: 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 | 0.5686 | 0.6 | 0.5981 |
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+ | No log | 0.01 | 100 | 0.5715 | 0.62 | 0.6205 |
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+ | No log | 0.01 | 150 | 0.5591 | 0.64 | 0.6400 |
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+ | No log | 0.01 | 200 | 0.5670 | 0.63 | 0.6288 |
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+ | No log | 0.02 | 250 | 0.5568 | 0.61 | 0.6106 |
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+ | No log | 0.02 | 300 | 0.5761 | 0.64 | 0.6383 |
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+ | No log | 0.02 | 350 | 0.5515 | 0.61 | 0.6106 |
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+ | No log | 0.03 | 400 | 0.5567 | 0.61 | 0.6087 |
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+ | No log | 0.03 | 450 | 0.5590 | 0.62 | 0.6192 |
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+ | 0.606 | 0.03 | 500 | 0.5454 | 0.64 | 0.6404 |
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+ | 0.606 | 0.04 | 550 | 0.5509 | 0.63 | 0.6303 |
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+ | 0.606 | 0.04 | 600 | 0.5451 | 0.64 | 0.6393 |
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+ | 0.606 | 0.04 | 650 | 0.5461 | 0.65 | 0.6488 |
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+ | 0.606 | 0.05 | 700 | 0.5443 | 0.62 | 0.6192 |
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+ | 0.606 | 0.05 | 750 | 0.5461 | 0.66 | 0.6593 |
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+ | 0.606 | 0.05 | 800 | 0.5420 | 0.66 | 0.6604 |
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+ | 0.606 | 0.06 | 850 | 0.5414 | 0.65 | 0.6502 |
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+ | 0.606 | 0.06 | 900 | 0.5411 | 0.65 | 0.6505 |
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+ | 0.606 | 0.06 | 950 | 0.5413 | 0.69 | 0.6834 |
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+ | 0.584 | 0.07 | 1000 | 0.5432 | 0.64 | 0.6353 |
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+ | 0.584 | 0.07 | 1050 | 0.5335 | 0.64 | 0.6383 |
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+ | 0.584 | 0.07 | 1100 | 0.5483 | 0.67 | 0.6702 |
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+ | 0.584 | 0.08 | 1150 | 0.5548 | 0.66 | 0.6605 |
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+ | 0.584 | 0.08 | 1200 | 0.5590 | 0.63 | 0.6306 |
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+ | 0.584 | 0.09 | 1250 | 0.5580 | 0.67 | 0.6697 |
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+ | 0.584 | 0.09 | 1300 | 0.5616 | 0.65 | 0.6502 |
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+ | 0.584 | 0.09 | 1350 | 0.5620 | 0.62 | 0.6131 |
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+ | 0.584 | 0.1 | 1400 | 0.5509 | 0.61 | 0.6059 |
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+ | 0.584 | 0.1 | 1450 | 0.5473 | 0.66 | 0.6605 |
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+ | 0.573 | 0.1 | 1500 | 0.5497 | 0.66 | 0.6593 |
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+ | 0.573 | 0.11 | 1550 | 0.5450 | 0.65 | 0.6502 |
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+ | 0.573 | 0.11 | 1600 | 0.5484 | 0.67 | 0.6689 |
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+ | 0.573 | 0.11 | 1650 | 0.5398 | 0.66 | 0.6584 |
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+ | 0.573 | 0.12 | 1700 | 0.5350 | 0.65 | 0.6477 |
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+ | 0.573 | 0.12 | 1750 | 0.5333 | 0.64 | 0.6370 |
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+ | 0.573 | 0.12 | 1800 | 0.5635 | 0.64 | 0.6400 |
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+ | 0.573 | 0.13 | 1850 | 0.5742 | 0.63 | 0.6297 |
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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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