16class_combo_111123_vthout_pp_tweet
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: 0.1399
- Accuracy: 0.9595
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: 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: 8
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 494 | 0.8411 | 0.7784 |
1.519 | 2.0 | 988 | 0.4959 | 0.8637 |
0.7315 | 3.0 | 1482 | 0.3370 | 0.9077 |
0.4973 | 4.0 | 1976 | 0.2599 | 0.9292 |
0.3755 | 5.0 | 2470 | 0.2055 | 0.9425 |
0.2998 | 6.0 | 2964 | 0.1649 | 0.9521 |
0.2492 | 7.0 | 3458 | 0.1491 | 0.9569 |
0.2062 | 8.0 | 3952 | 0.1399 | 0.9595 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
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Base model
google-bert/bert-base-multilingual-cased