End of training

README.md

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+---
+library_name: transformers
+license: cc-by-nc-4.0
+base_model: MCG-NJU/videomae-small-finetuned-kinetics
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: videomae-small-finetuned-kinetics-finetuned-judo
+  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-small-finetuned-kinetics-finetuned-judo
+
+This model is a fine-tuned version of [MCG-NJU/videomae-small-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-small-finetuned-kinetics) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2644
+- Accuracy: 0.8889
+
+## 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: 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: 130
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 0.6846        | 0.1077 | 14   | 0.6309          | 0.6667   |
+| 0.5857        | 1.1077 | 28   | 0.5324          | 0.7037   |
+| 0.3921        | 2.1077 | 42   | 0.5325          | 0.6296   |
+| 0.3011        | 3.1077 | 56   | 0.4113          | 0.8889   |
+| 0.2184        | 4.1077 | 70   | 0.3408          | 0.8889   |
+| 0.1523        | 5.1077 | 84   | 0.3739          | 0.8519   |
+| 0.1197        | 6.1077 | 98   | 0.3697          | 0.7778   |
+| 0.0763        | 7.1077 | 112  | 0.2562          | 0.8889   |
+| 0.0724        | 8.1077 | 126  | 0.2623          | 0.8889   |
+| 0.0685        | 9.0308 | 130  | 0.2644          | 0.8889   |
+
+
+### Framework versions
+
+- Transformers 4.47.1
+- Pytorch 2.5.1+cu124
+- Datasets 3.2.0
+- Tokenizers 0.21.0

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