distilbert-base-multilingual-cased_classification_finetuned_mobile01_all_adptive
This model is a fine-tuned version of distilbert/distilbert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2361
- F1: 0.9353
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.2946 | 1.0 | 909 | 0.2703 | 0.8938 |
| 0.2167 | 2.0 | 1818 | 0.2586 | 0.9249 |
| 0.1828 | 3.0 | 2727 | 0.2122 | 0.9308 |
| 0.1524 | 4.0 | 3636 | 0.2468 | 0.9305 |
| 0.1456 | 5.0 | 4545 | 0.2361 | 0.9353 |
| 0.1239 | 6.0 | 5454 | 0.2969 | 0.9336 |
| 0.0749 | 7.0 | 6363 | 0.3235 | 0.9326 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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