---
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: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# tibetan-code-switching-detector

This model is a fine-tuned version of [OMRIDRORI/mbert-tibetan-continual-unicode-240k](https://huggingface.co/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