End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: nateraw/videomae-base-finetuned-ucf101
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: videomae-base-finetuned-ucf101-finetuned-sports-videos-in-the-wild
+  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-finetuned-sports-videos-in-the-wild
+
+This model is a fine-tuned version of [nateraw/videomae-base-finetuned-ucf101](https://huggingface.co/nateraw/videomae-base-finetuned-ucf101) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1854
+- Accuracy: 0.7156
+- Macro Precision: 0.6435
+- Macro Recall: 0.6832
+- Macro F1: 0.6496
+- Weighted Precision: 0.7291
+- Weighted Recall: 0.7156
+- Weighted F1: 0.7123
+
+## 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: 0.0005
+- 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_ratio: 0.1
+- training_steps: 8400
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Accuracy | Macro Precision | Macro Recall | Macro F1 | Weighted Precision | Weighted Recall | Weighted F1 |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|:------------------:|:---------------:|:-----------:|
+| 1.3138        | 0.0501  | 421  | 1.4612          | 0.5567   | 0.5803          | 0.4927       | 0.4443   | 0.6651             | 0.5567          | 0.5304      |
+| 1.6466        | 1.0501  | 842  | 2.0129          | 0.4149   | 0.5145          | 0.4334       | 0.3690   | 0.6366             | 0.4149          | 0.4187      |
+| 2.011         | 2.0501  | 1263 | 1.7381          | 0.5133   | 0.4672          | 0.4727       | 0.4241   | 0.5597             | 0.5133          | 0.4856      |
+| 1.7608        | 3.0501  | 1684 | 1.5144          | 0.5578   | 0.5472          | 0.4672       | 0.4537   | 0.6215             | 0.5578          | 0.5480      |
+| 1.7314        | 4.0501  | 2105 | 1.6549          | 0.4816   | 0.4753          | 0.4554       | 0.4187   | 0.5675             | 0.4816          | 0.4706      |
+| 1.4126        | 5.0501  | 2526 | 1.6839          | 0.5126   | 0.4827          | 0.4714       | 0.4237   | 0.5870             | 0.5126          | 0.5113      |
+| 1.3559        | 6.0501  | 2947 | 1.4764          | 0.5742   | 0.5511          | 0.5145       | 0.4814   | 0.6425             | 0.5742          | 0.5695      |
+| 1.3796        | 7.0501  | 3368 | 1.6817          | 0.5064   | 0.5133          | 0.4921       | 0.4536   | 0.6268             | 0.5064          | 0.5253      |
+| 1.4973        | 8.0501  | 3789 | 1.4903          | 0.5520   | 0.5365          | 0.5120       | 0.4793   | 0.6410             | 0.5520          | 0.5587      |
+| 1.4502        | 9.0501  | 4210 | 1.3603          | 0.5921   | 0.5603          | 0.5687       | 0.5291   | 0.6589             | 0.5921          | 0.5989      |
+| 1.056         | 10.0501 | 4631 | 1.4150          | 0.5811   | 0.5584          | 0.5756       | 0.5269   | 0.6636             | 0.5811          | 0.5917      |
+| 0.8247        | 11.0501 | 5052 | 1.2276          | 0.6686   | 0.5981          | 0.6132       | 0.5821   | 0.6775             | 0.6686          | 0.6595      |
+| 0.8066        | 12.0501 | 5473 | 1.3814          | 0.6289   | 0.5689          | 0.5820       | 0.5502   | 0.6628             | 0.6289          | 0.6215      |
+| 0.735         | 13.0501 | 5894 | 1.3259          | 0.6424   | 0.5940          | 0.5780       | 0.5585   | 0.6813             | 0.6424          | 0.6373      |
+| 0.9272        | 14.0501 | 6315 | 1.2747          | 0.6664   | 0.6161          | 0.6330       | 0.5966   | 0.7183             | 0.6664          | 0.6715      |
+| 0.5165        | 15.0501 | 6736 | 1.2230          | 0.6923   | 0.6323          | 0.6416       | 0.6151   | 0.7109             | 0.6923          | 0.6867      |
+| 0.5818        | 16.0501 | 7157 | 1.3102          | 0.6642   | 0.6001          | 0.6261       | 0.5883   | 0.6979             | 0.6642          | 0.6652      |
+| 0.5303        | 17.0501 | 7578 | 1.1552          | 0.7178   | 0.6570          | 0.6744       | 0.6504   | 0.7264             | 0.7178          | 0.7124      |
+| 0.5301        | 18.0501 | 7999 | 1.2448          | 0.7014   | 0.6288          | 0.6740       | 0.6366   | 0.7171             | 0.7014          | 0.6987      |
+| 0.352         | 19.0477 | 8400 | 1.1854          | 0.7156   | 0.6435          | 0.6832       | 0.6496   | 0.7291             | 0.7156          | 0.7123      |
+
+
+### Framework versions
+
+- Transformers 4.51.3
+- Pytorch 2.1.0+cu118
+- Datasets 3.6.0
+- Tokenizers 0.21.1

model.safetensors

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