|
|
--- |
|
|
library_name: transformers |
|
|
license: apache-2.0 |
|
|
base_model: distilbert/distilbert-base-uncased |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- accuracy |
|
|
- precision |
|
|
- recall |
|
|
- f1 |
|
|
model-index: |
|
|
- name: distilbert_toxic |
|
|
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. --> |
|
|
|
|
|
# distilbert_toxic |
|
|
|
|
|
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.5048 |
|
|
- Accuracy: 0.8612 |
|
|
- Precision: 0.8469 |
|
|
- Recall: 0.8195 |
|
|
- F1: 0.8330 |
|
|
|
|
|
## 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: 32 |
|
|
- seed: 3407 |
|
|
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
|
- lr_scheduler_type: cosine |
|
|
- lr_scheduler_warmup_ratio: 0.1 |
|
|
- num_epochs: 4 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
|
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:| |
|
|
| 0.2971 | 1.0 | 4767 | 0.3258 | 0.8675 | 0.8643 | 0.8140 | 0.8384 | |
|
|
| 0.2798 | 2.0 | 9534 | 0.3120 | 0.8708 | 0.8452 | 0.8498 | 0.8475 | |
|
|
| 0.1481 | 3.0 | 14301 | 0.3898 | 0.8681 | 0.8466 | 0.8399 | 0.8432 | |
|
|
| 0.1161 | 4.0 | 19068 | 0.5048 | 0.8612 | 0.8469 | 0.8195 | 0.8330 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.56.1 |
|
|
- Pytorch 2.8.0+cu126 |
|
|
- Datasets 4.0.0 |
|
|
- Tokenizers 0.22.0 |
|
|
|
