skywalker290
commited on
End of training
Browse files- README.md +72 -0
- model.safetensors +1 -1
README.md
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---
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library_name: transformers
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license: cc-by-nc-4.0
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base_model: facebook/timesformer-base-finetuned-k400
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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-timesformer-d2
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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-timesformer-d2
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This model is a fine-tuned version of [facebook/timesformer-base-finetuned-k400](https://huggingface.co/facebook/timesformer-base-finetuned-k400) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.8173
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- Accuracy: 0.3661
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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: 6650
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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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| 2.3794 | 0.1 | 665 | 2.4547 | 0.1440 |
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| 2.5787 | 1.1 | 1330 | 2.5065 | 0.2607 |
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| 2.4653 | 2.1 | 1995 | 2.1117 | 0.3874 |
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| 2.3267 | 3.1 | 2660 | 2.3863 | 0.3567 |
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| 1.6617 | 4.1 | 3325 | 2.2500 | 0.3956 |
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| 1.3649 | 5.1 | 3990 | 2.7407 | 0.3711 |
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| 0.2922 | 6.1 | 4655 | 2.5032 | 0.4152 |
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| 0.6021 | 7.1 | 5320 | 3.3270 | 0.3529 |
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| 0.7572 | 8.1 | 5985 | 2.9130 | 0.4129 |
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| 1.1826 | 9.1 | 6650 | 2.8173 | 0.3661 |
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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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model.safetensors
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