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mvit_v2_s_Kinetics400_transf_BLANK_RWF-2000_DETECTION
DanJoshua/mvit_v2_s_Kinetics400_transf_BLANK_RWF-2000_DETECTION
mvit_v2_s_Kinetics400_transf_BLANK_RWF-2000_DETECTION is a machine learning model from DanJoshua. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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Updated Sep 8, 2024
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At a glance
- Library
- transformers
- Access
- Public
- Created
- Sep 7, 2024
- Updated
- Sep 8, 2024
- SHA
- 3a91618a
Model card
From the Hugging Face model README
<!-- 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. -->
mvit_v2_s_Kinetics400_transf_BLANK_RWF-2000_DETECTION
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2893
- Accuracy: 0.9075
- F1: 0.9075
- Precision: 0.9075
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: 1e-05
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 2280
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision |
|---|---|---|---|---|---|---|
| 0.6352 | 0.0667 | 152 | 0.4098 | 0.8688 | 0.8687 | 0.8693 |
| 0.3793 | 1.0667 | 304 | 0.3912 | 0.9 | 0.8994 | 0.9092 |
| 0.2673 | 2.0667 | 456 | 0.4216 | 0.8875 | 0.8864 | 0.9036 |
| 0.3411 | 3.0667 | 608 | 0.3268 | 0.9125 | 0.9125 | 0.9128 |
| 0.4172 | 4.0667 | 760 | 0.3353 | 0.9187 | 0.9186 | 0.9220 |
| 0.287 | 5.0667 | 912 | 0.3286 | 0.925 | 0.9247 | 0.9317 |
| 0.3292 | 6.0667 | 1064 | 0.3480 | 0.9187 | 0.9184 | 0.9268 |
| 0.132 | 7.0667 | 1216 | 0.3026 | 0.9437 | 0.9436 | 0.9472 |
| 0.357 | 8.0667 | 1368 | 0.3323 | 0.9313 | 0.9309 | 0.9396 |
| 0.2609 | 9.0667 | 1520 | 0.3071 | 0.9437 | 0.9436 | 0.9494 |
| 0.2457 | 10.0667 | 1672 | 0.3403 | 0.925 | 0.9246 | 0.9348 |
| 0.2192 | 11.0667 | 1824 | 0.3470 | 0.9313 | 0.9309 | 0.9396 |
| 0.2622 | 12.0667 | 1976 | 0.3427 | 0.9313 | 0.9309 | 0.9396 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.0.1+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1
- Library
- transformers
- Created
- Sep 7, 2024
- Updated
- Sep 8, 2024