proximity_cs_model_with_test
This model is a fine-tuned version of OMRIDRORI/mbert-tibetan-continual-unicode-240k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3626
- Accuracy: 0.9896
- Proximity F1: 0.2190
- Proximity Recall: 0.2370
- Proximity Precision: 0.2504
- Exact Matches: 0.6923
- Missed Switches: 0.5385
- False Switches: 2.4872
- Matches At 1 Words: 0.0
- Matches At 2 Words: 0.0
- Matches At 3 Words: 0.0
- Matches At 4 Words: 0.0
- Matches At 5 Words: 0.0
- Matches At 6 Words: 0.0
- Matches At 7 Words: 0.0
- Matches At 8 Words: 0.0
- Matches At 9 Words: 0.0
- Matches At 10 Words: 0.0
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 25
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Proximity F1 | Proximity Recall | Proximity Precision | Exact Matches | Missed Switches | False Switches | Matches At 1 Words | Matches At 2 Words | Matches At 3 Words | Matches At 4 Words | Matches At 5 Words | Matches At 6 Words | Matches At 7 Words | Matches At 8 Words | Matches At 9 Words | Matches At 10 Words |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.3554 | 7.6923 | 100 | 0.3063 | 0.9314 | 0.0892 | 0.3119 | 0.0543 | 1.0 | 0.0513 | 19.7179 | 0.0513 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0256 | 0.0 | 0.0 | 0.0256 | 0.0769 |
| 0.0729 | 15.3846 | 200 | 0.2531 | 0.9791 | 0.1595 | 0.2241 | 0.1791 | 0.6923 | 0.4872 | 5.5128 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0513 | 0.0 |
| 0.0156 | 23.0769 | 300 | 0.3626 | 0.9896 | 0.2190 | 0.2370 | 0.2504 | 0.6923 | 0.5385 | 2.4872 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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