File size: 4,321 Bytes
e664b3e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 |
---
library_name: transformers
license: mit
base_model: microsoft/deberta-v3-xsmall
tags:
- generated_from_trainer
model-index:
- name: capricious-gnu-139
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. -->
# capricious-gnu-139
This model is a fine-tuned version of [microsoft/deberta-v3-xsmall](https://huggingface.co/microsoft/deberta-v3-xsmall) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1831
- Hamming Loss: 0.0661
- Zero One Loss: 0.4537
- Jaccard Score: 0.4105
- Hamming Loss Optimised: 0.0659
- Hamming Loss Threshold: 0.6135
- Zero One Loss Optimised: 0.4087
- Zero One Loss Threshold: 0.4316
- Jaccard Score Optimised: 0.3479
- Jaccard Score Threshold: 0.3462
## 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: 5.0943791435964314e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 2024
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 9
### Training results
| Training Loss | Epoch | Step | Validation Loss | Hamming Loss | Zero One Loss | Jaccard Score | Hamming Loss Optimised | Hamming Loss Threshold | Zero One Loss Optimised | Zero One Loss Threshold | Jaccard Score Optimised | Jaccard Score Threshold |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:-------------:|:-------------:|:----------------------:|:----------------------:|:-----------------------:|:-----------------------:|:-----------------------:|:-----------------------:|
| 0.4159 | 1.0 | 100 | 0.3376 | 0.1123 | 1.0 | 1.0 | 0.1123 | 0.9000 | 1.0 | 0.9000 | 1.0 | 0.9000 |
| 0.3121 | 2.0 | 200 | 0.2841 | 0.0932 | 0.8113 | 0.8087 | 0.0931 | 0.4416 | 0.6963 | 0.1641 | 0.6101 | 0.1642 |
| 0.2602 | 3.0 | 300 | 0.2338 | 0.092 | 0.785 | 0.7819 | 0.0765 | 0.3980 | 0.6113 | 0.3139 | 0.5072 | 0.2086 |
| 0.2174 | 4.0 | 400 | 0.2063 | 0.0712 | 0.5975 | 0.5703 | 0.0698 | 0.4494 | 0.5363 | 0.3378 | 0.4363 | 0.2553 |
| 0.1896 | 5.0 | 500 | 0.1967 | 0.0694 | 0.5813 | 0.5551 | 0.0661 | 0.4552 | 0.4513 | 0.3622 | 0.3900 | 0.2346 |
| 0.1726 | 6.0 | 600 | 0.1910 | 0.07 | 0.4988 | 0.4614 | 0.0695 | 0.5944 | 0.4400 | 0.4036 | 0.3569 | 0.3149 |
| 0.1618 | 7.0 | 700 | 0.1861 | 0.0679 | 0.475 | 0.4339 | 0.0651 | 0.5430 | 0.4237 | 0.4130 | 0.3652 | 0.3483 |
| 0.1522 | 8.0 | 800 | 0.1845 | 0.0683 | 0.4712 | 0.4328 | 0.0663 | 0.5807 | 0.4337 | 0.4266 | 0.3585 | 0.3310 |
| 0.1484 | 9.0 | 900 | 0.1831 | 0.0661 | 0.4537 | 0.4105 | 0.0659 | 0.6135 | 0.4087 | 0.4316 | 0.3479 | 0.3462 |
### Framework versions
- Transformers 4.45.1
- Pytorch 2.5.1+cu118
- Datasets 3.1.0
- Tokenizers 0.20.3
|