|
--- |
|
license: apache-2.0 |
|
base_model: distilbert-base-uncased |
|
tags: |
|
- generated_from_trainer |
|
- sentiment analysis |
|
- cyberbullying detection |
|
- PyTorch |
|
- Trainer |
|
- DistilBERT |
|
model-index: |
|
- name: Training_Checkpoint |
|
results: [] |
|
language: |
|
- en |
|
metrics: |
|
- f1 |
|
- accuracy |
|
library_name: transformers |
|
pipeline_tag: text-classification |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# Training_Checkpoint |
|
|
|
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- eval_loss: 0.0006 |
|
- eval_accuracy: 1.0 |
|
- eval_f1: 1.0 |
|
- eval_runtime: 1.7344 |
|
- eval_samples_per_second: 576.552 |
|
- eval_steps_per_second: 36.323 |
|
- epoch: 10.0 |
|
- step: 630 |
|
|
|
## 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: 50 |
|
|
|
### Framework versions |
|
|
|
- Transformers 4.42.4 |
|
- Pytorch 2.3.1+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
