File size: 1,949 Bytes
3ca839a fda9aef 3ca839a fda9aef 3ca839a | 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 | ---
library_name: transformers
license: apache-2.0
base_model: timm/mobilenetv3_small_100.lamb_in1k
tags:
- image-classification
- vision
- timm
- trackio
- trackio:https://huggingface.co/spaces/evalstate/trackio
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ic-smoke-test
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. -->
<a href="https://huggingface.co/spaces/evalstate/trackio" target="_blank"><img src="https://raw.githubusercontent.com/gradio-app/trackio/refs/heads/main/trackio/assets/badge.png" alt="Visualize in Trackio" title="Visualize in Trackio" style="height: 40px;"/></a>
# ic-smoke-test
This model is a fine-tuned version of [timm/mobilenetv3_small_100.lamb_in1k](https://huggingface.co/timm/mobilenetv3_small_100.lamb_in1k) on the beans dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0278
- Accuracy: 0.54
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 7 | 1.0294 | 0.58 |
| No log | 2.0 | 14 | 1.0278 | 0.54 |
### Framework versions
- Transformers 5.3.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.4
- Tokenizers 0.22.2
|