roberta-base-mrpc / README.md
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---
language:
- en
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
base_model: roberta-base
model-index:
- name: roberta-base-mrpc
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: GLUE MRPC
type: glue
args: mrpc
metrics:
- type: accuracy
value: 0.9019607843137255
name: Accuracy
- type: f1
value: 0.9295774647887324
name: F1
- task:
type: natural-language-inference
name: Natural Language Inference
dataset:
name: glue
type: glue
config: mrpc
split: validation
metrics:
- type: accuracy
value: 0.9019607843137255
name: Accuracy
verified: true
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- type: precision
value: 0.9134948096885813
name: Precision
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiY2NmZThjNDI0YThmMzE4MjdhNjM3OTFmYzAwNzY4ZTM4ZDc4ZDA3NTYzYWRhNTdlNWMyZWI1NTMwZmFhNzQ5NyIsInZlcnNpb24iOjF9.nOkbqzXVD3r9LrIePn7o9Ny8_GiPoSBskCx3ey3Hrexrx00Gj6B9wkVvc8EcV5bAsBTeAJSeqO7ncS_-WJjlCQ
- type: recall
value: 0.946236559139785
name: Recall
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNzA2NDgzYTkzMTY4ZDQxYTdlZmM2ODY4YzM4N2E0ODk0YzRkNDI3YTFhMGIwNDZhNTI0MmIyNGU0YmFlMzRjYyIsInZlcnNpb24iOjF9.jNL0IQk6XnUd6zFfHwTSL41Ax35OdoE8xQA-2PqEFs9UtT2O9fo6cZyXDln6QPMGHOlwNgPp_PX6mLrmDHN6Cw
- type: auc
value: 0.9536411880747964
name: AUC
verified: true
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- type: f1
value: 0.9295774647887324
name: F1
verified: true
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- type: loss
value: 0.48942330479621887
name: loss
verified: true
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---
<!-- 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. -->
# mrpc
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4898
- Accuracy: 0.9020
- F1: 0.9296
- Combined Score: 0.9158
## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 5.0
### Training results
### Framework versions
- Transformers 4.20.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1