metadata
license: mit
base_model: microsoft/mdeberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-MDBT-TCR_data-cl-cardiff_cl_only
results: []
scenario-MDBT-TCR_data-cl-cardiff_cl_only
This model is a fine-tuned version of microsoft/mdeberta-v3-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 4.7992
- Accuracy: 0.5154
- F1: 0.5146
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: 64
- seed: 66
- 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 | 1.2801 | 0.5069 | 0.5029 |
| 0.7278 | 2.17 | 500 | 1.6260 | 0.5077 | 0.5080 |
| 0.7278 | 3.26 | 750 | 1.6500 | 0.5193 | 0.5209 |
| 0.3512 | 4.35 | 1000 | 2.1813 | 0.5123 | 0.5144 |
| 0.3512 | 5.43 | 1250 | 2.5133 | 0.5154 | 0.5167 |
| 0.1838 | 6.52 | 1500 | 2.6502 | 0.5093 | 0.5093 |
| 0.1838 | 7.61 | 1750 | 3.0408 | 0.5015 | 0.5021 |
| 0.118 | 8.7 | 2000 | 3.3486 | 0.4877 | 0.4822 |
| 0.118 | 9.78 | 2250 | 3.5117 | 0.4923 | 0.4906 |
| 0.072 | 10.87 | 2500 | 3.5966 | 0.5046 | 0.5027 |
| 0.072 | 11.96 | 2750 | 3.3823 | 0.5100 | 0.5121 |
| 0.0545 | 13.04 | 3000 | 3.7627 | 0.5085 | 0.5053 |
| 0.0545 | 14.13 | 3250 | 3.9342 | 0.5108 | 0.5124 |
| 0.0336 | 15.22 | 3500 | 4.2215 | 0.5093 | 0.5061 |
| 0.0336 | 16.3 | 3750 | 4.2219 | 0.5046 | 0.5021 |
| 0.0272 | 17.39 | 4000 | 4.0061 | 0.5208 | 0.5227 |
| 0.0272 | 18.48 | 4250 | 4.3214 | 0.5116 | 0.5074 |
| 0.0198 | 19.57 | 4500 | 4.5333 | 0.5093 | 0.5075 |
| 0.0198 | 20.65 | 4750 | 4.3535 | 0.5247 | 0.5256 |
| 0.0161 | 21.74 | 5000 | 4.5169 | 0.5239 | 0.5238 |
| 0.0161 | 22.83 | 5250 | 4.4982 | 0.5285 | 0.5298 |
| 0.012 | 23.91 | 5500 | 4.5591 | 0.5170 | 0.5186 |
| 0.012 | 25.0 | 5750 | 4.7615 | 0.5085 | 0.5069 |
| 0.0066 | 26.09 | 6000 | 4.8457 | 0.5100 | 0.5079 |
| 0.0066 | 27.17 | 6250 | 4.7872 | 0.5131 | 0.5118 |
| 0.0069 | 28.26 | 6500 | 4.6257 | 0.5301 | 0.5303 |
| 0.0069 | 29.35 | 6750 | 4.7992 | 0.5154 | 0.5146 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3