File size: 2,747 Bytes
9d0f897 4631756 9d0f897 4631756 9d0f897 4631756 9d0f897 4631756 9d0f897 |
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 77 78 79 80 81 82 83 84 |
---
library_name: transformers
license: apache-2.0
base_model: c14kevincardenas/ClimBEiTv2
tags:
- knowledge_distillation
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mobilevit-x-small_alpha0.5_temp3.0
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. -->
# mobilevit-x-small_alpha0.5_temp3.0
This model is a fine-tuned version of [c14kevincardenas/ClimBEiTv2](https://huggingface.co/c14kevincardenas/ClimBEiTv2) on the c14kevincardenas/beta_caller_284_person_crop_seq_withlimb_2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8309
- Accuracy: 0.6581
## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2144 | 1.0 | 90 | 1.3722 | 0.3103 |
| 1.1701 | 2.0 | 180 | 1.3059 | 0.3933 |
| 1.0635 | 3.0 | 270 | 1.1638 | 0.4792 |
| 0.9234 | 4.0 | 360 | 1.0532 | 0.5217 |
| 0.8136 | 5.0 | 450 | 0.9654 | 0.5711 |
| 0.7593 | 6.0 | 540 | 0.8966 | 0.6166 |
| 0.7131 | 7.0 | 630 | 0.8710 | 0.6334 |
| 0.6935 | 8.0 | 720 | 0.9317 | 0.5998 |
| 0.6504 | 9.0 | 810 | 0.8675 | 0.6294 |
| 0.6329 | 10.0 | 900 | 0.8388 | 0.6492 |
| 0.6021 | 11.0 | 990 | 0.8389 | 0.6522 |
| 0.5937 | 12.0 | 1080 | 0.8454 | 0.6462 |
| 0.5687 | 13.0 | 1170 | 0.8777 | 0.6393 |
| 0.5647 | 14.0 | 1260 | 0.8434 | 0.6354 |
| 0.5372 | 15.0 | 1350 | 0.8428 | 0.6561 |
| 0.5302 | 16.0 | 1440 | 0.8376 | 0.6512 |
| 0.5374 | 17.0 | 1530 | 0.8365 | 0.6561 |
| 0.5273 | 18.0 | 1620 | 0.8431 | 0.6611 |
| 0.5197 | 19.0 | 1710 | 0.8309 | 0.6581 |
| 0.5123 | 20.0 | 1800 | 0.8316 | 0.6670 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
|