|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- f1 |
|
model-index: |
|
- name: Hate-Speech-Detection-mpnet-basev2 |
|
results: [] |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# Hate-Speech-Detection-mpnet-basev2 |
|
|
|
This model is a fine-tuned version of [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4546 |
|
- Accuracy: 0.9320 |
|
- F1: 0.9317 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 15 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
|
| No log | 1.0 | 225 | 0.2916 | 0.8952 | 0.9027 | |
|
| No log | 2.0 | 450 | 0.2543 | 0.9153 | 0.9156 | |
|
| 0.2816 | 3.0 | 675 | 0.2853 | 0.9164 | 0.9158 | |
|
| 0.2816 | 4.0 | 900 | 0.3623 | 0.9197 | 0.9221 | |
|
| 0.0831 | 5.0 | 1125 | 0.4164 | 0.9186 | 0.9207 | |
|
| 0.0831 | 6.0 | 1350 | 0.4079 | 0.9208 | 0.9198 | |
|
| 0.0232 | 7.0 | 1575 | 0.4187 | 0.9275 | 0.9267 | |
|
| 0.0232 | 8.0 | 1800 | 0.4831 | 0.9231 | 0.9246 | |
|
| 0.0089 | 9.0 | 2025 | 0.4570 | 0.9298 | 0.9305 | |
|
| 0.0089 | 10.0 | 2250 | 0.4546 | 0.9320 | 0.9317 | |
|
| 0.0089 | 11.0 | 2475 | 0.5022 | 0.9264 | 0.9278 | |
|
| 0.0051 | 12.0 | 2700 | 0.5734 | 0.9208 | 0.9232 | |
|
| 0.0051 | 13.0 | 2925 | 0.5780 | 0.9186 | 0.9211 | |
|
| 0.002 | 14.0 | 3150 | 0.5049 | 0.9287 | 0.9295 | |
|
| 0.002 | 15.0 | 3375 | 0.5444 | 0.9231 | 0.9249 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.26.1 |
|
- Pytorch 2.0.1 |
|
- Datasets 2.10.1 |
|
- Tokenizers 0.13.3 |
|
|
