File size: 3,054 Bytes
d9adad3 |
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 |
---
library_name: transformers
license: mit
base_model: microsoft/deberta-v3-xsmall
tags:
- generated_from_trainer
model-index:
- name: resilient-rook-798
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. -->
# resilient-rook-798
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: 0.2372
- Hamming Loss: 0.0925
- Zero One Loss: 0.7925
- Jaccard Score: 0.79
- Hamming Loss Optimised: 0.0789
- Hamming Loss Threshold: 0.3524
- Zero One Loss Optimised: 0.5887
- Zero One Loss Threshold: 0.3038
- Jaccard Score Optimised: 0.5148
- Jaccard Score Threshold: 0.2378
## 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: 4
### 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 |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:-------------:|:-------------:|:----------------------:|:----------------------:|:-----------------------:|:-----------------------:|:-----------------------:|:-----------------------:|
| 0.4118 | 1.0 | 100 | 0.3355 | 0.1123 | 1.0 | 1.0 | 0.1123 | 0.9000 | 1.0 | 0.9000 | 1.0 | 0.9000 |
| 0.308 | 2.0 | 200 | 0.2855 | 0.0938 | 0.8125 | 0.81 | 0.0929 | 0.3525 | 0.7488 | 0.1661 | 0.6086 | 0.1537 |
| 0.2668 | 3.0 | 300 | 0.2478 | 0.0925 | 0.7913 | 0.7888 | 0.0865 | 0.3723 | 0.64 | 0.2728 | 0.5209 | 0.1919 |
| 0.2417 | 4.0 | 400 | 0.2372 | 0.0925 | 0.7925 | 0.79 | 0.0789 | 0.3524 | 0.5887 | 0.3038 | 0.5148 | 0.2378 |
### Framework versions
- Transformers 4.45.1
- Pytorch 2.5.1+cu118
- Datasets 3.1.0
- Tokenizers 0.20.3
|