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---
license: mit
base_model: microsoft/deberta-v3-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large_test_9e-6
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-v3-large_test_9e-6
This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1640
- Accuracy: 0.794
## 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: 9e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 310 | 0.6535 | 0.772 |
| 0.6202 | 2.0 | 620 | 0.6425 | 0.798 |
| 0.6202 | 3.0 | 930 | 0.7958 | 0.782 |
| 0.1527 | 4.0 | 1240 | 1.0140 | 0.796 |
| 0.0448 | 5.0 | 1550 | 1.0381 | 0.796 |
| 0.0448 | 6.0 | 1860 | 1.1083 | 0.798 |
| 0.017 | 7.0 | 2170 | 1.1640 | 0.794 |
### Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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