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---
license: mit
base_model: microsoft/deberta-v3-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: deberta-v3-large-262-ver1
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-262-ver1
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: 0.0768
- Precision: 0.9904
- Recall: 0.9904
- F1: 0.9904
- Accuracy: 0.9904
## 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: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0624 | 1.0 | 1287 | 0.0447 | 0.9907 | 0.9907 | 0.9907 | 0.9907 |
| 0.0272 | 2.0 | 2574 | 0.0899 | 0.9865 | 0.9865 | 0.9865 | 0.9865 |
| 0.0136 | 3.0 | 3861 | 0.0605 | 0.9894 | 0.9894 | 0.9894 | 0.9894 |
| 0.0071 | 4.0 | 5148 | 0.0771 | 0.9894 | 0.9894 | 0.9894 | 0.9894 |
| 0.0015 | 5.0 | 6435 | 0.0768 | 0.9904 | 0.9904 | 0.9904 | 0.9904 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.2.0
- Datasets 2.20.0
- Tokenizers 0.19.1
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