metadata
license: mit
tags:
- generated_from_trainer
datasets:
- amazon_reviews_multi
metrics:
- accuracy
model-index:
- name: deberta_amazon_reviews_v1
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: amazon_reviews_multi
type: amazon_reviews_multi
args: en
metrics:
- name: Accuracy
type: accuracy
value: 0.6184
deberta_amazon_reviews_v1
This model is a fine-tuned version of microsoft/deberta-v3-base on the amazon_reviews_multi dataset. It achieves the following results on the evaluation set:
- Loss: 0.9076
- Accuracy: 0.6184
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: 8
- 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_steps: 200
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9312 | 0.2 | 5000 | 0.9796 | 0.5856 |
| 0.9316 | 0.4 | 10000 | 0.9336 | 0.5974 |
| 0.9076 | 0.6 | 15000 | 0.9171 | 0.6026 |
| 0.9024 | 0.8 | 20000 | 0.9194 | 0.6046 |
| 0.8794 | 1.0 | 25000 | 0.9109 | 0.6084 |
| 0.8067 | 1.2 | 30000 | 0.9339 | 0.6092 |
| 0.8268 | 1.4 | 35000 | 0.9073 | 0.6162 |
| 0.8205 | 1.6 | 40000 | 0.9042 | 0.6158 |
| 0.795 | 1.8 | 45000 | 0.9189 | 0.6168 |
| 0.7836 | 2.0 | 50000 | 0.9076 | 0.6184 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6