| | --- |
| | license: mit |
| | base_model: xlm-roberta-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - f1 |
| | model-index: |
| | - name: HODravidianLangTech |
| | 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. --> |
| |
|
| | # HODravidianLangTech |
| |
|
| | This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.5859 |
| | - F1: 0.6908 |
| |
|
| | ## 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-06 |
| | - train_batch_size: 16 |
| | - eval_batch_size: 16 |
| | - seed: 1234 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 32 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - num_epochs: 20 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | F1 | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | | No log | 1.0 | 100 | 0.6926 | 0.3377 | |
| | | No log | 2.0 | 200 | 0.6916 | 0.5490 | |
| | | No log | 3.0 | 300 | 0.6856 | 0.6050 | |
| | | No log | 4.0 | 400 | 0.6701 | 0.6287 | |
| | | 0.6833 | 5.0 | 500 | 0.6601 | 0.6396 | |
| | | 0.6833 | 6.0 | 600 | 0.6511 | 0.6466 | |
| | | 0.6833 | 7.0 | 700 | 0.6447 | 0.6458 | |
| | | 0.6833 | 8.0 | 800 | 0.6250 | 0.6560 | |
| | | 0.6833 | 9.0 | 900 | 0.6113 | 0.6516 | |
| | | 0.624 | 10.0 | 1000 | 0.6051 | 0.6658 | |
| | | 0.624 | 11.0 | 1100 | 0.6075 | 0.6567 | |
| | | 0.624 | 12.0 | 1200 | 0.6038 | 0.6671 | |
| | | 0.624 | 13.0 | 1300 | 0.5997 | 0.6716 | |
| | | 0.624 | 14.0 | 1400 | 0.5949 | 0.6805 | |
| | | 0.5739 | 15.0 | 1500 | 0.5958 | 0.6885 | |
| | | 0.5739 | 16.0 | 1600 | 0.5924 | 0.6905 | |
| | | 0.5739 | 17.0 | 1700 | 0.5957 | 0.6875 | |
| | | 0.5739 | 18.0 | 1800 | 0.5839 | 0.6976 | |
| | | 0.5739 | 19.0 | 1900 | 0.5865 | 0.6908 | |
| | | 0.5598 | 20.0 | 2000 | 0.5859 | 0.6908 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.35.2 |
| | - Pytorch 2.1.0+cu118 |
| | - Datasets 2.15.0 |
| | - Tokenizers 0.15.0 |
| |
|
