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---
license: mit
tags:
- generated_from_trainer
model-index:
- name: deberta-classifier-feedback-1024-pseudo-final
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# deberta-classifier-feedback-1024-pseudo-final
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.
It achieves the following results on the evaluation set:
- Loss: 0.5263
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.5814 | 0.04 | 10 | 0.5888 |
| 0.5521 | 0.08 | 20 | 0.5736 |
| 0.5685 | 0.13 | 30 | 0.5809 |
| 0.6052 | 0.17 | 40 | 0.5702 |
| 0.5532 | 0.21 | 50 | 0.5571 |
| 0.6177 | 0.25 | 60 | 0.5848 |
| 0.6196 | 0.3 | 70 | 0.5464 |
| 0.5772 | 0.34 | 80 | 0.5307 |
| 0.5805 | 0.38 | 90 | 0.5550 |
| 0.6453 | 0.42 | 100 | 0.5467 |
| 0.5756 | 0.47 | 110 | 0.5587 |
| 0.5901 | 0.51 | 120 | 0.5482 |
| 0.568 | 0.55 | 130 | 0.5263 |
| 0.5452 | 0.59 | 140 | 0.5698 |
| 0.5949 | 0.64 | 150 | 0.5484 |
| 0.5537 | 0.68 | 160 | 0.5783 |
| 0.5327 | 0.72 | 170 | 0.5202 |
| 0.5449 | 0.76 | 180 | 0.5272 |
| 0.5345 | 0.81 | 190 | 0.5621 |
| 0.5837 | 0.85 | 200 | 0.5501 |
| 0.5969 | 0.89 | 210 | 0.5470 |
| 0.5905 | 0.93 | 220 | 0.5924 |
| 0.5481 | 0.97 | 230 | 0.5415 |
| 0.5035 | 1.02 | 240 | 0.5321 |
| 0.4508 | 1.06 | 250 | 0.5371 |
| 0.4227 | 1.1 | 260 | 0.5276 |
| 0.4423 | 1.14 | 270 | 0.5324 |
| 0.432 | 1.19 | 280 | 0.5378 |
| 0.4317 | 1.23 | 290 | 0.5302 |
| 0.46 | 1.27 | 300 | 0.5302 |
| 0.435 | 1.31 | 310 | 0.5326 |
| 0.3813 | 1.36 | 320 | 0.5431 |
| 0.4422 | 1.4 | 330 | 0.5323 |
| 0.4298 | 1.44 | 340 | 0.5575 |
| 0.5068 | 1.48 | 350 | 0.5529 |
| 0.4619 | 1.53 | 360 | 0.5589 |
| 0.4852 | 1.57 | 370 | 0.5256 |
| 0.3888 | 1.61 | 380 | 0.5731 |
| 0.4319 | 1.65 | 390 | 0.5335 |
| 0.4422 | 1.69 | 400 | 0.5419 |
| 0.4522 | 1.74 | 410 | 0.5547 |
| 0.4276 | 1.78 | 420 | 0.5263 |
| 0.3988 | 1.82 | 430 | 0.5481 |
| 0.4063 | 1.86 | 440 | 0.5404 |
| 0.4141 | 1.91 | 450 | 0.5292 |
| 0.4149 | 1.95 | 460 | 0.5241 |
| 0.4104 | 1.99 | 470 | 0.5263 |
### Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
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