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---
license: mit
base_model: microsoft/deberta-v3-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Classifier_with_external_sets_04
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. -->
# Classifier_with_external_sets_04
This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co./microsoft/deberta-v3-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2741
- Accuracy: 0.9193
## 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: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 26
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log | 0.9983 | 289 | 0.3540 | 0.8893 |
| 0.5256 | 2.0 | 579 | 0.3874 | 0.8673 |
| 0.5256 | 2.9983 | 868 | 0.3275 | 0.8991 |
| 0.378 | 4.0 | 1158 | 0.3244 | 0.9028 |
| 0.378 | 4.9983 | 1447 | 0.4013 | 0.8312 |
| 0.4029 | 6.0 | 1737 | 0.4052 | 0.8428 |
| 0.3932 | 6.9983 | 2026 | 0.3667 | 0.8801 |
| 0.3932 | 8.0 | 2316 | 0.3972 | 0.8385 |
| 0.3972 | 8.9983 | 2605 | 0.3983 | 0.8648 |
| 0.3972 | 10.0 | 2895 | 0.3805 | 0.8587 |
| 0.3734 | 10.9983 | 3184 | 0.3735 | 0.8746 |
| 0.3734 | 12.0 | 3474 | 0.3256 | 0.8893 |
| 0.3752 | 12.9983 | 3763 | 0.2800 | 0.9101 |
| 0.3169 | 14.0 | 4053 | 0.3071 | 0.8979 |
| 0.3169 | 14.9983 | 4342 | 0.3083 | 0.9052 |
| 0.312 | 16.0 | 4632 | 0.2894 | 0.9168 |
| 0.312 | 16.9983 | 4921 | 0.3725 | 0.8624 |
| 0.3162 | 18.0 | 5211 | 0.3163 | 0.8979 |
| 0.3185 | 18.9983 | 5500 | 0.3030 | 0.8991 |
| 0.3185 | 20.0 | 5790 | 0.3045 | 0.8997 |
| 0.2951 | 20.9983 | 6079 | 0.2944 | 0.9076 |
| 0.2951 | 22.0 | 6369 | 0.2693 | 0.9199 |
| 0.2916 | 22.9983 | 6658 | 0.2711 | 0.9187 |
| 0.2916 | 24.0 | 6948 | 0.2651 | 0.9211 |
| 0.2593 | 24.9983 | 7237 | 0.2696 | 0.9193 |
| 0.2646 | 25.9551 | 7514 | 0.2741 | 0.9193 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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