| | --- |
| | license: mit |
| | base_model: FacebookAI/xlm-roberta-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | model-index: |
| | - name: XMLRoberta_70KURL |
| | 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. --> |
| |
|
| | # XMLRoberta_70KURL |
| | |
| | This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.4150 |
| | - Accuracy: 0.9408 |
| | - F1: 0.9448 |
| | |
| | ## 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: 64 |
| | - eval_batch_size: 64 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 128 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 2150 |
| | - num_epochs: 20 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| | |:-------------:|:-------:|:----:|:---------------:|:--------:|:------:| |
| | | No log | 0.4651 | 200 | 0.4701 | 0.8955 | 0.8673 | |
| | | No log | 0.9302 | 400 | 0.1893 | 0.9359 | 0.9368 | |
| | | No log | 1.3953 | 600 | 0.2241 | 0.9128 | 0.9192 | |
| | | No log | 1.8605 | 800 | 0.2777 | 0.8848 | 0.8984 | |
| | | 0.382 | 2.3256 | 1000 | 0.1388 | 0.9504 | 0.9525 | |
| | | 0.382 | 2.7907 | 1200 | 0.1028 | 0.9694 | 0.9701 | |
| | | 0.382 | 3.2558 | 1400 | 0.1413 | 0.9557 | 0.9579 | |
| | | 0.382 | 3.7209 | 1600 | 0.0929 | 0.9718 | 0.9722 | |
| | | 0.1521 | 4.1860 | 1800 | 0.1008 | 0.9695 | 0.9702 | |
| | | 0.1521 | 4.6512 | 2000 | 0.1939 | 0.9238 | 0.9306 | |
| | | 0.1521 | 5.1163 | 2200 | 0.1550 | 0.9401 | 0.9443 | |
| | | 0.1521 | 5.5814 | 2400 | 0.0813 | 0.9744 | 0.9750 | |
| | | 0.1044 | 6.0465 | 2600 | 0.2088 | 0.9193 | 0.9267 | |
| | | 0.1044 | 6.5116 | 2800 | 0.1343 | 0.9523 | 0.9548 | |
| | | 0.1044 | 6.9767 | 3000 | 0.2172 | 0.9219 | 0.9289 | |
| | | 0.1044 | 7.4419 | 3200 | 0.1097 | 0.9656 | 0.9668 | |
| | | 0.1044 | 7.9070 | 3400 | 0.3044 | 0.9147 | 0.9230 | |
| | | 0.0762 | 8.3721 | 3600 | 0.2122 | 0.9283 | 0.9341 | |
| | | 0.0762 | 8.8372 | 3800 | 0.1430 | 0.9532 | 0.9556 | |
| | | 0.0762 | 9.3023 | 4000 | 0.2332 | 0.9312 | 0.9368 | |
| | | 0.0762 | 9.7674 | 4200 | 0.2167 | 0.9297 | 0.9353 | |
| | | 0.0564 | 10.2326 | 4400 | 0.1904 | 0.9475 | 0.9506 | |
| | | 0.0564 | 10.6977 | 4600 | 0.2916 | 0.9196 | 0.9270 | |
| | | 0.0564 | 11.1628 | 4800 | 0.2317 | 0.9451 | 0.9484 | |
| | | 0.0564 | 11.6279 | 5000 | 0.2430 | 0.9475 | 0.9503 | |
| | | 0.042 | 12.0930 | 5200 | 0.4035 | 0.9248 | 0.9315 | |
| | | 0.042 | 12.5581 | 5400 | 0.3060 | 0.9352 | 0.9398 | |
| | | 0.042 | 13.0233 | 5600 | 0.2894 | 0.9359 | 0.9407 | |
| | | 0.042 | 13.4884 | 5800 | 0.2804 | 0.9439 | 0.9474 | |
| | | 0.042 | 13.9535 | 6000 | 0.2941 | 0.9456 | 0.9490 | |
| | | 0.0316 | 14.4186 | 6200 | 0.3211 | 0.9424 | 0.9460 | |
| | | 0.0316 | 14.8837 | 6400 | 0.3453 | 0.9371 | 0.9416 | |
| | | 0.0316 | 15.3488 | 6600 | 0.2587 | 0.9548 | 0.9569 | |
| | | 0.0316 | 15.8140 | 6800 | 0.3433 | 0.9432 | 0.9468 | |
| | | 0.025 | 16.2791 | 7000 | 0.3454 | 0.9416 | 0.9455 | |
| | | 0.025 | 16.7442 | 7200 | 0.2977 | 0.9450 | 0.9484 | |
| | | 0.025 | 17.2093 | 7400 | 0.3622 | 0.9452 | 0.9486 | |
| | | 0.025 | 17.6744 | 7600 | 0.3035 | 0.9550 | 0.9572 | |
| | | 0.0196 | 18.1395 | 7800 | 0.3588 | 0.9464 | 0.9496 | |
| | | 0.0196 | 18.6047 | 8000 | 0.3714 | 0.9467 | 0.9500 | |
| | | 0.0196 | 19.0698 | 8200 | 0.4517 | 0.9341 | 0.9391 | |
| | | 0.0196 | 19.5349 | 8400 | 0.4078 | 0.9411 | 0.9451 | |
| | | 0.0148 | 20.0 | 8600 | 0.4150 | 0.9408 | 0.9448 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.41.2 |
| | - Pytorch 2.1.2 |
| | - Datasets 2.19.2 |
| | - Tokenizers 0.19.1 |
| | |
