---
language:
- en
license: mit
tags:
- generated_from_trainer
- deberta-v3
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: deberta-v3-small
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE MRPC
      type: glue
      args: mrpc
    metrics:
    - type: accuracy
      value: 0.8921568627450981
      name: Accuracy
    - type: f1
      value: 0.9233449477351917
      name: F1
  - task:
      type: natural-language-inference
      name: Natural Language Inference
    dataset:
      name: glue
      type: glue
      config: mrpc
      split: validation
    metrics:
    - type: accuracy
      value: 0.8921568627450981
      name: Accuracy
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZmQ3MjM2NTJiZjJmM2UxYTlmMDczOTQ2MjY4OTdhZTAyM2RiMTc2YjZiNWIwZDk1ZGUxMjgzMDBiOWVjZTQ4OCIsInZlcnNpb24iOjF9.yerN7Izy0yT3ykyO3t5Mr-TO3oxpTMfijCWJKnA_XO_rt81LP3-9qbqknXur6ahHqKN-1BLtr_fmAu0-IPQyDA
    - type: precision
      value: 0.8983050847457628
      name: Precision
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZWQxODVmYTM4OThlMjNhY2MzZTBhMWJmMmNjMDMyYjYyNzc4NWI3YzJjZDkzMTcyOWEwN2IxOWYyOGQ5NTY5MSIsInZlcnNpb24iOjF9.cfqvd8wnSqhHj5fKlIb6JN9He8ooAu94tFJytw2I93qqGSVvaTktM0Ib_DqPuHYneGY1DGbgb6Nsl90DiZSMCQ
    - type: recall
      value: 0.9498207885304659
      name: Recall
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNjg3Y2Y1NGY0NTRjMWFhYTAxMWYxMTcxNWM2ZDU5NGY1ZTk3OTJmZWQyYmIzMGJiZWQ0YWQ2MjNhOGU2MGU0ZCIsInZlcnNpb24iOjF9.jj7VNaWQU3u3tnngqCixlfkwF8h6ykzvHm4tgezJe1pacAU0Tsugn7IPvAJTrvNE0sU8_Q7dm-C_UKQGzmlIBw
    - type: auc
      value: 0.9516129032258065
      name: AUC
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMDhkOTQ0ZmVlYTYwNTdjY2IxYTM5ZThhYzgzZWMxMGQzMThmZDkwNTcyMWZiNzg4Y2I3NjZhMzVjYmNmN2FlZiIsInZlcnNpb24iOjF9.28hOJFgnyNHXMpaFbNTEcolUcuNVqrXNSuT6hTs2vrjlAIWVnzxUfaHjH2kVYh1-sOSNSE9maetd1CtQ7i78CQ
    - type: f1
      value: 0.9233449477351917
      name: F1
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZmY0ZWE5Y2Q5YmZlOWM4OTU0OGIwOWEwNDk3MTlkYTY5YzgwMjQwNDFjYWU4ZDdmZWY4Nzc0MzQzMTM2YTRhYyIsInZlcnNpb24iOjF9.NymiR2fVXaI6ytAGZFM8HuQLxTJlxuUsWziVNaauyuJ9xfOLOGVJ6VI_H7CoBwc-pZKbKiQOvtfpOGwt1J22CA
    - type: loss
      value: 0.2787226438522339
      name: loss
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZGNhMDgyMGI3ZWI4NDVkYzM0NjE1ZTk0YjczYzU4NmRhOGYxM2RlMjU3YThhY2QzNmU3NmJhM2IzMWI5MDMwNyIsInZlcnNpb24iOjF9.HFdpBkvu0671KUgkOtpSgeGBr3wU7g51zVt3-wEwVWhS4hMX4oPFAqF4JBxFx3mgbGjTDiRQ2xiA5lm0UnkdCg
---

<!-- 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