|
--- |
|
license: apache-2.0 |
|
base_model: distilbert-base-uncased |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- yahoo_answers_topics |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: deberta_finetuned_yahoo_answers_topics |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: yahoo_answers_topics |
|
type: yahoo_answers_topics |
|
config: yahoo_answers_topics |
|
split: test |
|
args: yahoo_answers_topics |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.71195 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# deberta_finetuned_yahoo_answers_topics |
|
|
|
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the yahoo_answers_topics dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.9096 |
|
- Accuracy: 0.7119 |
|
|
|
## 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 |
|
- training_steps: 30000 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
|
| 1.1025 | 0.03 | 5000 | 1.0702 | 0.6717 | |
|
| 1.0132 | 0.06 | 10000 | 0.9976 | 0.6834 | |
|
| 0.8688 | 0.09 | 15000 | 0.9770 | 0.6961 | |
|
| 0.9964 | 0.11 | 20000 | 0.9356 | 0.7020 | |
|
| 0.9338 | 0.14 | 25000 | 0.9259 | 0.7090 | |
|
| 0.9059 | 0.17 | 30000 | 0.9096 | 0.7119 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.34.1 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.14.1 |
|
|
