End of training
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README.md
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---
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library_name: transformers
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license: mit
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base_model: google/vivit-b-16x2-kinetics400
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: vivit-vivit-d1
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# vivit-vivit-d1
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This model is a fine-tuned version of [google/vivit-b-16x2-kinetics400](https://huggingface.co/google/vivit-b-16x2-kinetics400) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.5318
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- Accuracy: 0.8134
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 1
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- eval_batch_size: 1
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- seed: 42
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- training_steps: 12010
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|
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| 0.0323 | 0.1 | 1201 | 1.9695 | 0.6636 |
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| 1.051 | 1.1 | 2402 | 1.8521 | 0.7380 |
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| 0.0027 | 2.1 | 3603 | 1.9220 | 0.6500 |
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| 0.0008 | 3.1 | 4804 | 1.3982 | 0.7767 |
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| 1.1999 | 4.1 | 6005 | 1.5625 | 0.6924 |
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| 0.0004 | 5.1 | 7206 | 1.4784 | 0.7614 |
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| 0.0188 | 6.1 | 8407 | 1.3777 | 0.7882 |
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| 0.6328 | 7.1 | 9608 | 1.6121 | 0.7761 |
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| 0.8161 | 8.1 | 10809 | 1.7552 | 0.7670 |
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| 0.0001 | 9.1 | 12010 | 1.5318 | 0.8134 |
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### Framework versions
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- Transformers 4.46.2
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- Pytorch 2.5.1+cu124
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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