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---
language:
- en
license: mit
tags:
- generated_from_trainer
- deberta-v3
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: deberta-v3-small
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
args: mrpc
metrics:
- name: Accuracy
type: accuracy
value: 0.8921568627450981
- name: F1
type: f1
value: 0.9233449477351917
- task:
type: natural-language-inference
name: Natural Language Inference
dataset:
name: glue
type: glue
config: mrpc
split: validation
metrics:
- name: Accuracy
type: accuracy
value: 0.8921568627450981
verified: true
- name: Precision
type: precision
value: 0.8983050847457628
verified: true
- name: Recall
type: recall
value: 0.9498207885304659
verified: true
- name: AUC
type: auc
value: 0.9516129032258065
verified: true
- name: F1
type: f1
value: 0.9233449477351917
verified: true
- name: loss
type: loss
value: 0.2787226438522339
verified: true
---
<!-- 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 (small) fine-tuned on MRPC
This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2787
- Accuracy: 0.8922
- F1: 0.9233
- Combined Score: 0.9078
## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| No log | 1.0 | 230 | 0.2787 | 0.8922 | 0.9233 | 0.9078 |
| No log | 2.0 | 460 | 0.3651 | 0.875 | 0.9137 | 0.8944 |
| No log | 3.0 | 690 | 0.5238 | 0.8799 | 0.9179 | 0.8989 |
| No log | 4.0 | 920 | 0.4712 | 0.8946 | 0.9222 | 0.9084 |
| 0.2147 | 5.0 | 1150 | 0.5704 | 0.8946 | 0.9262 | 0.9104 |
| 0.2147 | 6.0 | 1380 | 0.5697 | 0.8995 | 0.9284 | 0.9140 |
| 0.2147 | 7.0 | 1610 | 0.6651 | 0.8922 | 0.9214 | 0.9068 |
| 0.2147 | 8.0 | 1840 | 0.6726 | 0.8946 | 0.9239 | 0.9093 |
| 0.0183 | 9.0 | 2070 | 0.7250 | 0.8848 | 0.9177 | 0.9012 |
| 0.0183 | 10.0 | 2300 | 0.7093 | 0.8922 | 0.9223 | 0.9072 |
### Framework versions
- Transformers 4.13.0.dev0
- Pytorch 1.10.0+cu111
- Datasets 1.15.1
- Tokenizers 0.10.3
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