End of training

README.md

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+---
+library_name: transformers
+license: cc-by-nc-4.0
+base_model: MCG-NJU/videomae-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+model-index:
+- name: videomae-base-finetuned-ucf-crimevbinary-balancedv6
+  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. -->
+
+# videomae-base-finetuned-ucf-crimevbinary-balancedv6
+
+This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6175
+- Accuracy: 0.8475
+- Precision: 0.8572
+- Recall: 0.8475
+- Auc: 0.9263
+
+## 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: 3e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 30
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Auc    |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.5676        | 1.0   | 165  | 0.5685          | 0.6608   | 0.6975    | 0.6608 | 0.8059 |
+| 0.5645        | 2.0   | 330  | 0.3607          | 0.8481   | 0.8509    | 0.8481 | 0.9362 |
+| 0.4638        | 3.0   | 495  | 0.5746          | 0.8021   | 0.8226    | 0.8021 | 0.8919 |
+| 0.5765        | 4.0   | 660  | 0.3634          | 0.8622   | 0.8626    | 0.8622 | 0.9262 |
+| 0.4146        | 5.0   | 825  | 0.5092          | 0.8092   | 0.8302    | 0.8092 | 0.9225 |
+| 0.4319        | 6.0   | 990  | 0.4897          | 0.8799   | 0.8811    | 0.8799 | 0.9316 |
+| 0.3396        | 7.0   | 1155 | 0.5233          | 0.8587   | 0.8599    | 0.8587 | 0.9257 |
+| 0.1152        | 8.0   | 1320 | 0.6568          | 0.8763   | 0.8767    | 0.8763 | 0.9190 |
+| 0.0578        | 9.0   | 1485 | 0.6344          | 0.8693   | 0.8716    | 0.8693 | 0.9321 |
+| 0.0029        | 10.0  | 1650 | 0.7321          | 0.8728   | 0.8739    | 0.8728 | 0.9280 |
+| 0.1363        | 11.0  | 1815 | 0.7399          | 0.8622   | 0.8636    | 0.8622 | 0.9215 |
+
+
+### Framework versions
+
+- Transformers 4.47.0.dev0
+- Pytorch 2.5.1+cu124
+- Datasets 3.1.0
+- Tokenizers 0.20.3

model.safetensors

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