End of training

README.md

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+---
+license: mit
+base_model: google/vivit-b-16x2-kinetics400
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: vivit-b-16x2-kinetics400_training_O_OM_0519
+  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. -->
+
+# vivit-b-16x2-kinetics400_training_O_OM_0519
+
+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.
+It achieves the following results on the evaluation set:
+- Loss: 1.1012
+- Accuracy: 0.815
+
+## 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: 2
+- eval_batch_size: 2
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- training_steps: 3000
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.9097        | 0.1   | 300  | 0.9219          | 0.64     |
+| 0.0229        | 1.1   | 600  | 0.7215          | 0.83     |
+| 0.0019        | 2.1   | 900  | 0.9705          | 0.815    |
+| 0.2377        | 3.1   | 1200 | 1.0544          | 0.815    |
+| 0.0002        | 4.1   | 1500 | 1.1033          | 0.8      |
+| 0.0003        | 5.1   | 1800 | 1.0511          | 0.82     |
+| 0.0002        | 6.1   | 2100 | 1.0354          | 0.805    |
+| 0.0033        | 7.1   | 2400 | 1.1037          | 0.81     |
+| 0.0002        | 8.1   | 2700 | 1.0985          | 0.815    |
+| 0.0002        | 9.1   | 3000 | 1.1012          | 0.815    |
+
+
+### Framework versions
+
+- Transformers 4.40.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

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