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---
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-base-zeroshot-v2.0-2024-03-21-22-15
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-base-zeroshot-v2.0-2024-03-21-22-15
This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1169
- F1 Macro: 0.5016
- F1 Micro: 0.5474
- Accuracy Balanced: 0.5434
- Accuracy: 0.5474
- Precision Macro: 0.6345
- Recall Macro: 0.5434
- Precision Micro: 0.5474
- Recall Micro: 0.5474
## 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: 16
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | Accuracy Balanced | Accuracy | Precision Macro | Recall Macro | Precision Micro | Recall Micro |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:|
| 0.2288 | 1.0 | 27331 | 0.6189 | 0.7688 | 0.7881 | 0.7705 | 0.7881 | 0.7673 | 0.7705 | 0.7881 | 0.7881 |
| 0.1559 | 2.0 | 54662 | 0.6059 | 0.7896 | 0.8082 | 0.7898 | 0.8082 | 0.7894 | 0.7898 | 0.8082 | 0.8082 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.2+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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