metadata
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- f1
model-index:
- name: deberta-finetuned-answer-polarity-7e6
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: answer_pol
split: validation
args: answer_pol
metrics:
- name: F1
type: f1
value: 0.8625097340010413
deberta-finetuned-answer-polarity-7e6
This model is a fine-tuned version of microsoft/deberta-large on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.9143
- F1: 0.8625
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: 7e-06
- train_batch_size: 16
- eval_batch_size: 16
- 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 | F1 |
---|---|---|---|---|
No log | 1.0 | 214 | 0.6748 | 0.8696 |
0.0795 | 2.0 | 428 | 0.8541 | 0.8512 |
0.0508 | 3.0 | 642 | 0.9143 | 0.8625 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3