tat
This model is a fine-tuned version of google-bert/bert-base-multilingual-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3164
- F1-micro: 0.3349
- F1-macro: 0.2353
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 4
Training results
Training Loss | Epoch | Step | Validation Loss | F1-micro | F1-macro |
---|---|---|---|---|---|
0.5547 | 1.0 | 25 | 0.3898 | 0.0 | 0.0 |
0.3766 | 2.0 | 50 | 0.3570 | 0.0 | 0.0 |
0.3383 | 3.0 | 75 | 0.3265 | 0.2316 | 0.1630 |
0.312 | 4.0 | 100 | 0.3164 | 0.3349 | 0.2353 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1
- Downloads last month
- 7
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
Model tree for jaycentg/tat
Base model
google-bert/bert-base-multilingual-uncased