|
|
--- |
|
|
license: apache-2.0 |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- accuracy |
|
|
- precision |
|
|
- recall |
|
|
- f1 |
|
|
model-index: |
|
|
- name: mbert-profane-final |
|
|
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. --> |
|
|
|
|
|
# mbert-profane-final |
|
|
|
|
|
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.4464 |
|
|
- Accuracy: 0.8983 |
|
|
- Precision: 0.8135 |
|
|
- Recall: 0.8120 |
|
|
- F1: 0.8128 |
|
|
|
|
|
## 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: 1e-05 |
|
|
- train_batch_size: 32 |
|
|
- eval_batch_size: 32 |
|
|
- seed: 42 |
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: linear |
|
|
- num_epochs: 10 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
|
|
| No log | 1.0 | 296 | 0.2313 | 0.9154 | 0.8687 | 0.8010 | 0.8294 | |
|
|
| 0.3077 | 2.0 | 592 | 0.2223 | 0.9125 | 0.8473 | 0.8205 | 0.8330 | |
|
|
| 0.3077 | 3.0 | 888 | 0.2137 | 0.9259 | 0.8784 | 0.8379 | 0.8563 | |
|
|
| 0.2102 | 4.0 | 1184 | 0.2334 | 0.9163 | 0.8483 | 0.8417 | 0.8449 | |
|
|
| 0.2102 | 5.0 | 1480 | 0.2737 | 0.9068 | 0.8305 | 0.8242 | 0.8273 | |
|
|
| 0.1533 | 6.0 | 1776 | 0.3214 | 0.8964 | 0.8034 | 0.8510 | 0.8239 | |
|
|
| 0.1092 | 7.0 | 2072 | 0.3409 | 0.9002 | 0.8115 | 0.8414 | 0.8252 | |
|
|
| 0.1092 | 8.0 | 2368 | 0.3849 | 0.9049 | 0.8322 | 0.8066 | 0.8185 | |
|
|
| 0.0775 | 9.0 | 2664 | 0.4408 | 0.8983 | 0.8113 | 0.8215 | 0.8162 | |
|
|
| 0.0775 | 10.0 | 2960 | 0.4464 | 0.8983 | 0.8135 | 0.8120 | 0.8128 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.24.0.dev0 |
|
|
- Pytorch 1.11.0+cu102 |
|
|
- Datasets 2.6.1 |
|
|
- Tokenizers 0.13.1 |
|
|
|
