metadata
license: apache-2.0
tags:
- text-classification
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: distilroberta-base-mrpc-glue-keith-alec
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: mrpc
split: validation
args: mrpc
metrics:
- name: Accuracy
type: accuracy
value: 0.8529411764705882
- name: F1
type: f1
value: 0.8958333333333334
distilroberta-base-mrpc-glue-keith-alec
This model is a fine-tuned version of distilroberta-base on the glue and the mrpc datasets. It achieves the following results on the evaluation set:
- Loss: 0.6392
- Accuracy: 0.8529
- F1: 0.8958
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-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.3596 | 1.09 | 500 | 1.1183 | 0.8309 | 0.8848 |
| 0.3241 | 2.18 | 1000 | 0.6392 | 0.8529 | 0.8958 |
| 0.1673 | 3.27 | 1500 | 0.7843 | 0.8431 | 0.8869 |
| 0.0807 | 4.36 | 2000 | 0.9659 | 0.8456 | 0.8916 |
Framework versions
- Transformers 4.29.0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.13.3