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
+model-index:
+- name: videomae-base-finetuned-ucf101-subset
+  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-ucf101-subset
+
+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: 0.0888
+- Accuracy: 0.9857
+
+## 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: 6
+- eval_batch_size: 6
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 12
+- optimizer: Use OptimizerNames.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_ratio: 0.1
+- training_steps: 750
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 4.3003        | 0.0333 | 25   | 1.8220          | 0.5429   |
+| 2.4578        | 1.0333 | 50   | 1.1173          | 0.6571   |
+| 1.7213        | 2.0333 | 75   | 0.8284          | 0.6      |
+| 1.0839        | 3.0333 | 100  | 0.5795          | 0.7571   |
+| 0.6657        | 4.0333 | 125  | 0.2759          | 0.9714   |
+| 0.138         | 5.0333 | 150  | 0.1465          | 0.9714   |
+| 0.1764        | 6.0333 | 175  | 0.0888          | 0.9857   |
+| 0.0474        | 7.0333 | 200  | 0.2699          | 0.8857   |
+| 0.1228        | 8.0333 | 225  | 0.0644          | 0.9857   |
+| 0.0597        | 9.0333 | 250  | 0.1139          | 0.9714   |
+
+
+### Framework versions
+
+- Transformers 4.47.1
+- Pytorch 2.6.0+cu124
+- Datasets 3.2.0
+- Tokenizers 0.21.0

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