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---
library_name: transformers
license: apache-2.0
base_model: c14kevincardenas/ClimBEiTv2
tags:
- knowledge_distillation
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mobilevit-small_alpha0.7_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-small_alpha0.7_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: 0.8524
- Accuracy: 0.6660
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1499 | 1.0 | 90 | 1.4251 | 0.2460 |
| 1.0997 | 2.0 | 180 | 1.3384 | 0.3251 |
| 1.0075 | 3.0 | 270 | 1.2409 | 0.3864 |
| 0.8689 | 4.0 | 360 | 1.0919 | 0.4980 |
| 0.7581 | 5.0 | 450 | 1.0005 | 0.5652 |
| 0.7002 | 6.0 | 540 | 0.9315 | 0.6038 |
| 0.6484 | 7.0 | 630 | 0.9005 | 0.6166 |
| 0.6085 | 8.0 | 720 | 0.9252 | 0.5988 |
| 0.5562 | 9.0 | 810 | 0.8605 | 0.6630 |
| 0.5352 | 10.0 | 900 | 0.8696 | 0.6265 |
| 0.514 | 11.0 | 990 | 0.8557 | 0.6571 |
| 0.4819 | 12.0 | 1080 | 0.8793 | 0.6294 |
| 0.4538 | 13.0 | 1170 | 0.8856 | 0.6354 |
| 0.4382 | 14.0 | 1260 | 0.8554 | 0.6581 |
| 0.4349 | 15.0 | 1350 | 0.8707 | 0.6393 |
| 0.4122 | 16.0 | 1440 | 0.8568 | 0.6640 |
| 0.4101 | 17.0 | 1530 | 0.8540 | 0.6630 |
| 0.3922 | 18.0 | 1620 | 0.8543 | 0.6621 |
| 0.3929 | 19.0 | 1710 | 0.8524 | 0.6660 |
| 0.3965 | 20.0 | 1800 | 0.8661 | 0.6512 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
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