End of training

README.md

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+---
+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: 1.9424
+- Accuracy: 0.5333
+
+## 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: 3
+- eval_batch_size: 3
+- 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: 800
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.5319        | 0.1   | 80   | 0.9986          | 0.5      |
+| 0.5747        | 1.1   | 160  | 1.1108          | 0.5167   |
+| 0.4534        | 2.1   | 240  | 1.3027          | 0.4833   |
+| 0.2058        | 3.1   | 320  | 2.2119          | 0.5      |
+| 0.504         | 4.1   | 400  | 2.3382          | 0.5167   |
+| 0.377         | 5.1   | 480  | 1.6407          | 0.65     |
+| 0.8547        | 6.1   | 560  | 2.3820          | 0.5      |
+| 0.4046        | 7.1   | 640  | 1.9771          | 0.5333   |
+| 0.006         | 8.1   | 720  | 2.0629          | 0.55     |
+| 0.0123        | 9.1   | 800  | 1.9424          | 0.5333   |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.1.2+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.1

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