|
--- |
|
license: apache-2.0 |
|
base_model: agvidit1/DistilledBert_HateSpeech_pretrain |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- hate_speech18 |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: distilbert-hate_speech18 |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: hate_speech18 |
|
type: hate_speech18 |
|
config: default |
|
split: train |
|
args: default |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.8587751371115173 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# distilbert-hate_speech18 |
|
|
|
This model is a fine-tuned version of [agvidit1/DistilledBert_HateSpeech_pretrain](https://huggingface.co/agvidit1/DistilledBert_HateSpeech_pretrain) on the hate_speech18 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4684 |
|
- Accuracy: 0.8588 |
|
|
|
## 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: 5.050180626898551e-06 |
|
- train_batch_size: 32 |
|
- eval_batch_size: 16 |
|
- seed: 33 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 8 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.4404 | 1.0 | 240 | 0.4670 | 0.8533 | |
|
| 0.4356 | 2.0 | 480 | 0.4642 | 0.8675 | |
|
| 0.4303 | 3.0 | 720 | 0.4649 | 0.8748 | |
|
| 0.4282 | 4.0 | 960 | 0.4694 | 0.8592 | |
|
| 0.4273 | 5.0 | 1200 | 0.4638 | 0.8729 | |
|
| 0.4256 | 6.0 | 1440 | 0.4651 | 0.8679 | |
|
| 0.425 | 7.0 | 1680 | 0.4682 | 0.8560 | |
|
| 0.4227 | 8.0 | 1920 | 0.4684 | 0.8588 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.36.0.dev0 |
|
- Pytorch 2.1.1 |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.15.0 |
|
|
