metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: hasoc19-bert-base-multilingual-cased-profane-new
results: []
hasoc19-bert-base-multilingual-cased-profane-new
This model is a fine-tuned version of bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5065
- Accuracy: 0.9030
- Precision: 0.8465
- Recall: 0.8330
- F1: 0.8395
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 | 0.2873 | 0.8954 | 0.8513 | 0.7881 | 0.8140 |
| 0.2999 | 2.0 | 592 | 0.2556 | 0.9078 | 0.8703 | 0.8149 | 0.8385 |
| 0.2999 | 3.0 | 888 | 0.2595 | 0.9106 | 0.8613 | 0.8415 | 0.8509 |
| 0.1945 | 4.0 | 1184 | 0.2682 | 0.9078 | 0.8601 | 0.8302 | 0.8439 |
| 0.1945 | 5.0 | 1480 | 0.3286 | 0.9087 | 0.8590 | 0.8365 | 0.8471 |
| 0.142 | 6.0 | 1776 | 0.3911 | 0.9002 | 0.8390 | 0.8351 | 0.8370 |
| 0.0944 | 7.0 | 2072 | 0.4184 | 0.9068 | 0.8558 | 0.8334 | 0.8439 |
| 0.0944 | 8.0 | 2368 | 0.4763 | 0.9011 | 0.8450 | 0.8261 | 0.8350 |
| 0.0631 | 9.0 | 2664 | 0.4952 | 0.9002 | 0.8412 | 0.8293 | 0.8351 |
| 0.0631 | 10.0 | 2960 | 0.5065 | 0.9030 | 0.8465 | 0.8330 | 0.8395 |
Framework versions
- Transformers 4.24.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.6.1
- Tokenizers 0.13.1