metadata
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-KD-PR-MSV-D2_data-cl-cardiff_cl_only_beta-jason
results: []
scenario-KD-PR-MSV-D2_data-cl-cardiff_cl_only_beta-jason
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 15.7103
- Accuracy: 0.4028
- F1: 0.4028
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: 6666
- 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 | 11.8668 | 0.3897 | 0.3820 |
| 13.776 | 2.17 | 500 | 11.3224 | 0.3873 | 0.3811 |
| 13.776 | 3.26 | 750 | 10.7331 | 0.3881 | 0.3824 |
| 11.4609 | 4.35 | 1000 | 11.7060 | 0.4035 | 0.4015 |
| 11.4609 | 5.43 | 1250 | 11.1579 | 0.3997 | 0.3802 |
| 9.9802 | 6.52 | 1500 | 11.6003 | 0.4066 | 0.4061 |
| 9.9802 | 7.61 | 1750 | 11.6088 | 0.4059 | 0.4048 |
| 8.6874 | 8.7 | 2000 | 11.9784 | 0.3904 | 0.3814 |
| 8.6874 | 9.78 | 2250 | 12.2923 | 0.4113 | 0.4097 |
| 7.5941 | 10.87 | 2500 | 13.1464 | 0.3858 | 0.3823 |
| 7.5941 | 11.96 | 2750 | 12.8350 | 0.3966 | 0.3946 |
| 6.5229 | 13.04 | 3000 | 13.1611 | 0.3850 | 0.3819 |
| 6.5229 | 14.13 | 3250 | 14.1517 | 0.4005 | 0.3995 |
| 5.6501 | 15.22 | 3500 | 14.0929 | 0.4005 | 0.3930 |
| 5.6501 | 16.3 | 3750 | 14.1956 | 0.4074 | 0.4070 |
| 4.9968 | 17.39 | 4000 | 13.8417 | 0.4043 | 0.4040 |
| 4.9968 | 18.48 | 4250 | 14.3873 | 0.3897 | 0.3879 |
| 4.4769 | 19.57 | 4500 | 15.4822 | 0.4244 | 0.4226 |
| 4.4769 | 20.65 | 4750 | 15.1566 | 0.3958 | 0.3952 |
| 3.9676 | 21.74 | 5000 | 14.8283 | 0.4159 | 0.4135 |
| 3.9676 | 22.83 | 5250 | 15.2368 | 0.3927 | 0.3928 |
| 3.6886 | 23.91 | 5500 | 15.4609 | 0.4005 | 0.4006 |
| 3.6886 | 25.0 | 5750 | 14.7384 | 0.4059 | 0.4038 |
| 3.4119 | 26.09 | 6000 | 15.4645 | 0.3858 | 0.3857 |
| 3.4119 | 27.17 | 6250 | 15.9168 | 0.3974 | 0.3967 |
| 3.1245 | 28.26 | 6500 | 15.4980 | 0.3920 | 0.3923 |
| 3.1245 | 29.35 | 6750 | 15.7103 | 0.4028 | 0.4028 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3