hasoc19-bert-base-multilingual-cased-HatredStatement-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: 0.6565
- Accuracy: 0.7319
- Precision: 0.7320
- Recall: 0.7319
- F1: 0.7307
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: 6
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
No log | 1.0 | 296 | 0.5540 | 0.7110 | 0.7147 | 0.7110 | 0.7067 |
0.5551 | 2.0 | 592 | 0.5345 | 0.7224 | 0.7673 | 0.7224 | 0.7038 |
0.5551 | 3.0 | 888 | 0.5752 | 0.7272 | 0.7430 | 0.7272 | 0.7183 |
0.4252 | 4.0 | 1184 | 0.5697 | 0.7376 | 0.7384 | 0.7376 | 0.7359 |
0.4252 | 5.0 | 1480 | 0.6335 | 0.7319 | 0.7388 | 0.7319 | 0.7269 |
0.3401 | 6.0 | 1776 | 0.6565 | 0.7319 | 0.7320 | 0.7319 | 0.7307 |
Framework versions
- Transformers 4.24.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.6.1
- Tokenizers 0.13.1
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