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---
license: mit
base_model: MoritzLaurer/DeBERTa-v3-large-mnli-fever-anli-ling-wanli
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 10k-finetune
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. -->
# 10k-finetune
This model is a fine-tuned version of [MoritzLaurer/DeBERTa-v3-large-mnli-fever-anli-ling-wanli](https://huggingface.co/MoritzLaurer/DeBERTa-v3-large-mnli-fever-anli-ling-wanli) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3357
- Accuracy: 0.8730
## 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: 5e-06
- train_batch_size: 2
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 16
- 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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4093 | 0.33 | 20 | 0.4616 | 0.8115 |
| 0.2952 | 0.66 | 40 | 0.3984 | 0.8238 |
| 0.2775 | 0.99 | 60 | 0.3357 | 0.8730 |
| 0.1836 | 1.32 | 80 | 0.3674 | 0.8402 |
| 0.1772 | 1.65 | 100 | 0.3687 | 0.8361 |
| 0.1502 | 1.98 | 120 | 0.3730 | 0.8443 |
| 0.1245 | 2.31 | 140 | 0.3966 | 0.8402 |
| 0.1226 | 2.64 | 160 | 0.3719 | 0.8566 |
| 0.1166 | 2.98 | 180 | 0.3768 | 0.8484 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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