scenario-NON-KD-SCR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_alpha
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 6.7853
- Accuracy: 0.3580
- F1: 0.3378
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 1123
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
No log | 1.09 | 250 | 1.1518 | 0.3495 | 0.3449 |
1.0509 | 2.17 | 500 | 1.5848 | 0.3665 | 0.3279 |
1.0509 | 3.26 | 750 | 2.0537 | 0.3673 | 0.3351 |
0.4971 | 4.35 | 1000 | 2.6254 | 0.3642 | 0.3389 |
0.4971 | 5.43 | 1250 | 3.3984 | 0.3495 | 0.3056 |
0.189 | 6.52 | 1500 | 3.9545 | 0.3588 | 0.3213 |
0.189 | 7.61 | 1750 | 4.3147 | 0.3634 | 0.3250 |
0.0832 | 8.7 | 2000 | 4.5326 | 0.3495 | 0.3223 |
0.0832 | 9.78 | 2250 | 4.8999 | 0.3627 | 0.3396 |
0.0407 | 10.87 | 2500 | 5.2749 | 0.3503 | 0.3354 |
0.0407 | 11.96 | 2750 | 5.2814 | 0.3634 | 0.3500 |
0.0279 | 13.04 | 3000 | 5.3923 | 0.3657 | 0.3502 |
0.0279 | 14.13 | 3250 | 5.7450 | 0.3565 | 0.3397 |
0.0153 | 15.22 | 3500 | 5.6113 | 0.3681 | 0.3582 |
0.0153 | 16.3 | 3750 | 5.1689 | 0.3704 | 0.3615 |
0.0145 | 17.39 | 4000 | 5.8264 | 0.3650 | 0.3579 |
0.0145 | 18.48 | 4250 | 5.6710 | 0.3650 | 0.3603 |
0.0092 | 19.57 | 4500 | 6.0070 | 0.3650 | 0.3547 |
0.0092 | 20.65 | 4750 | 6.2579 | 0.3519 | 0.3287 |
0.0034 | 21.74 | 5000 | 6.3540 | 0.3650 | 0.3550 |
0.0034 | 22.83 | 5250 | 6.4666 | 0.3619 | 0.3438 |
0.0031 | 23.91 | 5500 | 6.6982 | 0.3580 | 0.3286 |
0.0031 | 25.0 | 5750 | 6.6139 | 0.3657 | 0.3611 |
0.0016 | 26.09 | 6000 | 6.6320 | 0.3688 | 0.3632 |
0.0016 | 27.17 | 6250 | 6.7619 | 0.3673 | 0.3544 |
0.0015 | 28.26 | 6500 | 6.7368 | 0.3627 | 0.3426 |
0.0015 | 29.35 | 6750 | 6.7853 | 0.3580 | 0.3378 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
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