metadata
library_name: transformers
base_model: OMRIDRORI/mbert-tibetan-continual-unicode-240k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: tibetan-code-switching-detector
results: []
tibetan-code-switching-detector
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: 0.7828
- Accuracy: 0.8124
- Proximity F1: 0.0772
- Proximity Recall: 0.2920
- Proximity Precision: 0.0457
- Exact Matches: 0.7963
- Missed Switches: 0.0556
- False Switches: 14.7685
- Matches At 1 Words: 0.0093
- Matches At 2 Words: 0.0
- Matches At 3 Words: 0.0
- Matches At 4 Words: 0.0
- Matches At 5 Words: 0.0093
- 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: 1e-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: 1000
- num_epochs: 10
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1.4889 | 4.5977 | 200 | 0.9309 | 0.8405 | 0.1133 | 0.1649 | 0.0959 | 0.3981 | 0.3611 | 4.5741 | 0.0093 | 0.0 | 0.0 | 0.0093 | 0.0185 | 0.0185 | 0.0 | 0.0 | 0.0556 | 0.0 |
| 0.8272 | 9.1954 | 400 | 0.7828 | 0.8124 | 0.0772 | 0.2920 | 0.0457 | 0.7963 | 0.0556 | 14.7685 | 0.0093 | 0.0 | 0.0 | 0.0 | 0.0093 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 2.0.0
- Tokenizers 0.20.3