---
library_name: transformers
base_model: OMRIDRORI/mbert-tibetan-continual-unicode-240k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: tibetan_code_switching_model
  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_model

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: 0.3714
- Accuracy: 0.9445
- Switch Precision: 0.9381
- Switch Recall: 0.9725
- Switch F1: 0.9550
- True Switches: 109
- Pred Switches: 113
- Tp: 106
- Fp: 7
- Fn: 3

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- 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: 100
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Switch Precision | Switch Recall | Switch F1 | True Switches | Pred Switches | Tp  | Fp   | Fn |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----------------:|:-------------:|:---------:|:-------------:|:-------------:|:---:|:----:|:--:|
| 4.727         | 1.0   | 50   | 5.6020          | 0.2133   | 0.0749           | 0.9908        | 0.1393    | 109           | 1442          | 108 | 1334 | 1  |
| 1.7867        | 2.0   | 100  | 1.2875          | 0.5304   | 0.5365           | 0.9450        | 0.6844    | 109           | 192           | 103 | 89   | 6  |
| 1.1232        | 3.0   | 150  | 0.9034          | 0.6356   | 0.6835           | 0.9908        | 0.8090    | 109           | 158           | 108 | 50   | 1  |
| 0.7733        | 4.0   | 200  | 0.6946          | 0.7664   | 0.6855           | 1.0           | 0.8134    | 109           | 159           | 109 | 50   | 0  |
| 0.5582        | 5.0   | 250  | 0.4907          | 0.8514   | 0.7219           | 1.0           | 0.8385    | 109           | 151           | 109 | 42   | 0  |
| 0.4037        | 6.0   | 300  | 0.4428          | 0.8808   | 0.7219           | 1.0           | 0.8385    | 109           | 151           | 109 | 42   | 0  |
| 0.2593        | 7.0   | 350  | 0.3282          | 0.9213   | 0.8134           | 1.0           | 0.8971    | 109           | 134           | 109 | 25   | 0  |
| 0.1714        | 8.0   | 400  | 0.3918          | 0.9044   | 0.8244           | 0.9908        | 0.9000    | 109           | 131           | 108 | 23   | 1  |
| 0.1114        | 9.0   | 450  | 0.3473          | 0.9334   | 0.8710           | 0.9908        | 0.9270    | 109           | 124           | 108 | 16   | 1  |
| 0.0678        | 10.0  | 500  | 0.3275          | 0.9348   | 0.9145           | 0.9817        | 0.9469    | 109           | 117           | 107 | 10   | 2  |
| 0.075         | 11.0  | 550  | 0.3718          | 0.9392   | 0.8917           | 0.9817        | 0.9345    | 109           | 120           | 107 | 13   | 2  |
| 0.0276        | 12.0  | 600  | 0.3588          | 0.9435   | 0.9068           | 0.9817        | 0.9427    | 109           | 118           | 107 | 11   | 2  |
| 0.0251        | 13.0  | 650  | 0.3488          | 0.9411   | 0.9304           | 0.9817        | 0.9554    | 109           | 115           | 107 | 8    | 2  |
| 0.0154        | 14.0  | 700  | 0.3599          | 0.9455   | 0.9386           | 0.9817        | 0.9596    | 109           | 114           | 107 | 7    | 2  |
| 0.0165        | 15.0  | 750  | 0.3714          | 0.9445   | 0.9381           | 0.9725        | 0.9550    | 109           | 113           | 106 | 7    | 3  |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 2.0.0
- Tokenizers 0.20.3