metadata
language:
- en
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: deberta-v3-small
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE SST2
type: glue
args: sst2
metrics:
- name: Accuracy
type: accuracy
value: 0.9403669724770642
deberta-v3-small
This model is a fine-tuned version of microsoft/deberta-v3-small on the GLUE SST2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2134
- Accuracy: 0.9404
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: 5.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.176 | 1.0 | 4210 | 0.2134 | 0.9404 |
| 0.1254 | 2.0 | 8420 | 0.2362 | 0.9415 |
| 0.0957 | 3.0 | 12630 | 0.3187 | 0.9335 |
| 0.0673 | 4.0 | 16840 | 0.3039 | 0.9266 |
| 0.0457 | 5.0 | 21050 | 0.3521 | 0.9312 |
Framework versions
- Transformers 4.13.0.dev0
- Pytorch 1.10.0+cu111
- Datasets 1.15.1
- Tokenizers 0.10.3