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---
language: 
- en
tags:
- text-classification
metrics:
- accuracy
datasets:
- snli-1.0
- multi-nli-1.0
- nli-fever
- anli-v1.0

---

## deberta-v3-large-snli_mnli_fever_anli_R1_R2_R3-nli

#### Datasets
Based on microsoft/deberta-v3-large, this model was trained on the snli-v1.0, multi-nli-1.0, nli-fever and anli-1.0-r1/anli-1.0-r2/anli-1.0-r3 datasets, with the training weights of 1,1,1,10,20,10 respectively.  
The training codes are mostly referenced from: https://github.com/facebookresearch/anli

#### Hyperparameters
learning_rate: 1e-5  
max_length: 156  
batch_size: 16  
warmup_ratio: 0.1   
weight_decay: 0.0   
num_epochs: 2

#### Dev results
snli-v1.0 | multi-nli-1.0-m | multi-nli-1.0-mm | anli-1.0-r1 | anli-1.0-r2 | anli-1.0-r3
----------|-----------------|------------------|-------------|-------------|------------
0.938 | 0.914 | 0.912 | 0.796 | 0.627 | 0.610

#### Test results
Results of the test sets are shown together with some other official pre-trained model checkpoints.
Model | snli-v1.0 | anli-1.0-r1 | anli-1.0-r2 | anli-1.0-r3
------|-----------|-------------|-------------|------------
ynie/roberta-large-snli_mnli_fever_anli_R1_R2_R3-nli | - | 0.736 | 0.493 | 0.455
ynie/xlnet-large-cased-snli_mnli_fever_anli_R1_R2_R3-nli | - | 0.700 | 0.514 | 0.498
ynie/albert-xxlarge-v2-snli_mnli_fever_anli_R1_R2_R3-nli | - | 0.736 | 0.586 | 0.534
deberta-v3-large-snli_mnli_fever_anli_R1_R2_R3-nli | 0.929 | 0.775 | 0.636 | 0.612