metadata
license: apache-2.0
tags:
- text-classification
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: NLP_sequence_clasiffication
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: 0.8504901960784313
- name: F1
type: f1
value: 0.8872458410351203
NLP_sequence_clasiffication
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: 0.5325
- Accuracy: 0.8505
- F1: 0.8872
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.5129 | 1.09 | 500 | 0.7246 | 0.8113 | 0.8679 |
| 0.3526 | 2.18 | 1000 | 0.5325 | 0.8505 | 0.8872 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.13.3