Model save

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. -->
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/siccimo/huggingface/runs/65akq4kx)
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/siccimo/huggingface/runs/65akq4kx)
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/siccimo/huggingface/runs/65akq4kx)
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/siccimo/huggingface/runs/65akq4kx)
+# 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: 0.2589
+- Accuracy: 0.9097
+
+## 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: 16
+- eval_batch_size: 16
+- 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: 148
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 2.0115        | 0.1284 | 19   | 1.5469          | 0.5429   |
+| 1.2145        | 1.1284 | 38   | 0.9201          | 0.7      |
+| 0.6166        | 2.1284 | 57   | 0.5548          | 0.8286   |
+| 0.3255        | 3.1284 | 76   | 0.3556          | 0.9      |
+| 0.1945        | 4.1284 | 95   | 0.2918          | 0.8857   |
+| 0.098         | 5.1284 | 114  | 0.3874          | 0.8714   |
+| 0.0571        | 6.1284 | 133  | 0.1540          | 0.9571   |
+| 0.0387        | 7.1014 | 148  | 0.2547          | 0.8571   |
+
+
+### Framework versions
+
+- Transformers 4.42.3
+- Pytorch 2.1.2
+- Datasets 2.20.0
+- Tokenizers 0.19.1

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runs/Jul19_11-52-50_c85a676f2b00/events.out.tfevents.1721390865.c85a676f2b00.34.6

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