---
license: other
base_model: google/mobilenet_v2_1.0_224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mobilenet_v2-activity-recognition
  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. -->

# mobilenet_v2-activity-recognition

This model is a fine-tuned version of [google/mobilenet_v2_1.0_224](https://huggingface.co/google/mobilenet_v2_1.0_224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0450
- Accuracy: 0.6718

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 2.8136        | 0.1778 | 10   | 2.7919          | 0.0733   |
| 2.8041        | 0.3556 | 20   | 2.7240          | 0.1043   |
| 2.6841        | 0.5333 | 30   | 2.6304          | 0.1421   |
| 2.5799        | 0.7111 | 40   | 2.4856          | 0.2497   |
| 2.4537        | 0.8889 | 50   | 2.3143          | 0.3431   |
| 2.2593        | 1.0667 | 60   | 2.1425          | 0.4005   |
| 2.0671        | 1.2444 | 70   | 1.9995          | 0.4360   |
| 1.8958        | 1.4222 | 80   | 1.8545          | 0.4683   |
| 1.7891        | 1.6    | 90   | 1.7437          | 0.4939   |
| 1.6659        | 1.7778 | 100  | 1.6373          | 0.5317   |
| 1.6006        | 1.9556 | 110  | 1.5372          | 0.5568   |
| 1.4752        | 2.1333 | 120  | 1.4766          | 0.5705   |
| 1.3654        | 2.3111 | 130  | 1.4303          | 0.5862   |
| 1.3452        | 2.4889 | 140  | 1.3513          | 0.6048   |
| 1.3134        | 2.6667 | 150  | 1.3941          | 0.5663   |
| 1.2905        | 2.8444 | 160  | 1.2859          | 0.6159   |
| 1.2201        | 3.0222 | 170  | 1.2661          | 0.6174   |
| 1.1225        | 3.2    | 180  | 1.2662          | 0.6181   |
| 1.0991        | 3.3778 | 190  | 1.1911          | 0.6392   |
| 1.1171        | 3.5556 | 200  | 1.2437          | 0.6142   |
| 1.0643        | 3.7333 | 210  | 1.1952          | 0.6318   |
| 1.1095        | 3.9111 | 220  | 1.1333          | 0.6519   |
| 1.0284        | 4.0889 | 230  | 1.1642          | 0.6362   |
| 0.9896        | 4.2667 | 240  | 1.1140          | 0.6519   |
| 0.9507        | 4.4444 | 250  | 1.0811          | 0.6672   |
| 0.9437        | 4.6222 | 260  | 1.0729          | 0.6652   |
| 0.9522        | 4.8    | 270  | 1.0724          | 0.6650   |
| 0.953         | 4.9778 | 280  | 1.0645          | 0.6713   |
| 0.8857        | 5.1556 | 290  | 1.1049          | 0.6508   |
| 0.907         | 5.3333 | 300  | 1.0808          | 0.6580   |
| 0.8723        | 5.5111 | 310  | 1.0437          | 0.6766   |
| 0.824         | 5.6889 | 320  | 1.0227          | 0.6801   |
| 0.846         | 5.8667 | 330  | 1.0186          | 0.6746   |
| 0.845         | 6.0444 | 340  | 1.0166          | 0.6805   |
| 0.8015        | 6.2222 | 350  | 1.0379          | 0.6720   |
| 0.8798        | 6.4    | 360  | 0.9889          | 0.6879   |
| 0.8076        | 6.5778 | 370  | 1.0059          | 0.6829   |
| 0.8105        | 6.7556 | 380  | 1.0098          | 0.6783   |
| 0.7414        | 6.9333 | 390  | 0.9801          | 0.6859   |
| 0.7869        | 7.1111 | 400  | 0.9624          | 0.6993   |
| 0.7728        | 7.2889 | 410  | 1.0938          | 0.6547   |
| 0.7762        | 7.4667 | 420  | 0.9867          | 0.6825   |
| 0.7769        | 7.6444 | 430  | 1.0512          | 0.6670   |
| 0.7563        | 7.8222 | 440  | 1.0346          | 0.6770   |
| 0.762         | 8.0    | 450  | 1.0647          | 0.6597   |
| 0.726         | 8.1778 | 460  | 1.0134          | 0.6812   |
| 0.7515        | 8.3556 | 470  | 0.9921          | 0.6787   |
| 0.7034        | 8.5333 | 480  | 1.0043          | 0.6833   |
| 0.7426        | 8.7111 | 490  | 0.9721          | 0.6936   |
| 0.7225        | 8.8889 | 500  | 1.0450          | 0.6718   |
| 0.7372        | 9.0667 | 510  | 0.9957          | 0.6812   |
| 0.7238        | 9.2444 | 520  | 0.9928          | 0.6894   |
| 0.7824        | 9.4222 | 530  | 1.0413          | 0.6753   |
| 0.7218        | 9.6    | 540  | 0.9717          | 0.6877   |
| 0.6976        | 9.7778 | 550  | 0.9839          | 0.6859   |
| 0.7288        | 9.9556 | 560  | 1.0229          | 0.6728   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1