End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: google/vivit-b-16x2-kinetics400
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- recall
+- precision
+model-index:
+- name: vivit-b-16x2-kinetics400-finetuned-cricket_shot_detection_feb
+  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. -->
+
+# vivit-b-16x2-kinetics400-finetuned-cricket_shot_detection_feb
+
+This model is a fine-tuned version of [google/vivit-b-16x2-kinetics400](https://huggingface.co/google/vivit-b-16x2-kinetics400) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0740
+- Accuracy: 0.7333
+- F1: 0.7079
+- Recall: 0.7333
+- Precision: 0.7167
+
+## 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: 3e-06
+- train_batch_size: 2
+- eval_batch_size: 2
+- 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: 1445
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall | Precision |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
+| 1.35          | 0.2   | 289  | 1.4447          | 0.4      | 0.3476 | 0.4    | 0.3222    |
+| 0.8637        | 1.2   | 578  | 1.1747          | 0.5333   | 0.5137 | 0.5333 | 0.5278    |
+| 0.8758        | 2.2   | 867  | 1.0740          | 0.7333   | 0.7079 | 0.7333 | 0.7167    |
+| 0.5731        | 3.2   | 1156 | 1.0410          | 0.6      | 0.5746 | 0.6    | 0.5833    |
+| 0.7166        | 4.2   | 1445 | 1.0218          | 0.7333   | 0.7098 | 0.7333 | 0.7222    |
+
+
+### Framework versions
+
+- Transformers 4.47.0
+- Pytorch 2.6.0+cu124
+- Datasets 3.2.0
+- Tokenizers 0.21.0

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runs/Feb01_07-01-54_63e888fea0e8/events.out.tfevents.1738402161.63e888fea0e8.31.1

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