|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: bert-base-cased |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- liar |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: liar_binaryclassifier_distilbert_cased |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: liar |
|
type: liar |
|
config: default |
|
split: test |
|
args: default |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.6464208242950108 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# liar_binaryclassifier_distilbert_cased |
|
|
|
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the liar dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.6488 |
|
- Model Preparation Time: 0.0055 |
|
- Accuracy: 0.6464 |
|
|
|
## 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-06 |
|
- 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: 5 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:--------:| |
|
| 0.6836 | 1.0 | 461 | 0.6520 | 0.0055 | 0.6226 | |
|
| 0.6423 | 2.0 | 922 | 0.6326 | 0.0055 | 0.6399 | |
|
| 0.6091 | 3.0 | 1383 | 0.6362 | 0.0055 | 0.6443 | |
|
| 0.5843 | 4.0 | 1844 | 0.6422 | 0.0055 | 0.6551 | |
|
| 0.5624 | 5.0 | 2305 | 0.6488 | 0.0055 | 0.6464 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.2 |
|
- Pytorch 2.4.1+cu121 |
|
- Datasets 3.0.0 |
|
- Tokenizers 0.19.1 |
|
|
