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README.md
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---
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license: mit
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tags:
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- generated_from_trainer
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model-index:
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- name: deberta-classifier-feedback-1024-pseudo-final
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results: []
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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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# deberta-classifier-feedback-1024-pseudo-final
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This model is a fine-tuned version of [TTian/deberta-classifier-feedback-1024-pseudo](https://huggingface.co/TTian/deberta-classifier-feedback-1024-pseudo) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5263
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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: 2
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- total_train_batch_size: 16
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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: 2
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 0.5814 | 0.04 | 10 | 0.5888 |
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| 0.5521 | 0.08 | 20 | 0.5736 |
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| 0.5685 | 0.13 | 30 | 0.5809 |
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| 0.6052 | 0.17 | 40 | 0.5702 |
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| 0.5532 | 0.21 | 50 | 0.5571 |
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| 0.6177 | 0.25 | 60 | 0.5848 |
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| 0.6196 | 0.3 | 70 | 0.5464 |
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| 0.5772 | 0.34 | 80 | 0.5307 |
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| 0.5805 | 0.38 | 90 | 0.5550 |
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| 0.6453 | 0.42 | 100 | 0.5467 |
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| 0.5756 | 0.47 | 110 | 0.5587 |
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| 0.5901 | 0.51 | 120 | 0.5482 |
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| 0.568 | 0.55 | 130 | 0.5263 |
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| 0.5452 | 0.59 | 140 | 0.5698 |
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| 0.5949 | 0.64 | 150 | 0.5484 |
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| 0.5537 | 0.68 | 160 | 0.5783 |
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| 0.5327 | 0.72 | 170 | 0.5202 |
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| 0.5449 | 0.76 | 180 | 0.5272 |
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| 0.5345 | 0.81 | 190 | 0.5621 |
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| 0.5837 | 0.85 | 200 | 0.5501 |
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| 0.5969 | 0.89 | 210 | 0.5470 |
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| 0.5905 | 0.93 | 220 | 0.5924 |
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| 0.5481 | 0.97 | 230 | 0.5415 |
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| 0.5035 | 1.02 | 240 | 0.5321 |
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| 0.4508 | 1.06 | 250 | 0.5371 |
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| 0.4227 | 1.1 | 260 | 0.5276 |
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| 0.4423 | 1.14 | 270 | 0.5324 |
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| 0.432 | 1.19 | 280 | 0.5378 |
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| 0.4317 | 1.23 | 290 | 0.5302 |
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| 0.46 | 1.27 | 300 | 0.5302 |
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| 0.435 | 1.31 | 310 | 0.5326 |
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| 0.3813 | 1.36 | 320 | 0.5431 |
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| 0.4422 | 1.4 | 330 | 0.5323 |
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| 0.4298 | 1.44 | 340 | 0.5575 |
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| 0.5068 | 1.48 | 350 | 0.5529 |
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| 0.4619 | 1.53 | 360 | 0.5589 |
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| 0.4852 | 1.57 | 370 | 0.5256 |
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| 0.3888 | 1.61 | 380 | 0.5731 |
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| 0.4319 | 1.65 | 390 | 0.5335 |
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| 0.4422 | 1.69 | 400 | 0.5419 |
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| 0.4522 | 1.74 | 410 | 0.5547 |
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| 0.4276 | 1.78 | 420 | 0.5263 |
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| 0.3988 | 1.82 | 430 | 0.5481 |
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| 0.4063 | 1.86 | 440 | 0.5404 |
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| 0.4141 | 1.91 | 450 | 0.5292 |
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| 0.4149 | 1.95 | 460 | 0.5241 |
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| 0.4104 | 1.99 | 470 | 0.5263 |
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### Framework versions
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- Transformers 4.24.0
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- Pytorch 1.12.1+cu113
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- Datasets 2.7.1
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- Tokenizers 0.13.2
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