Model save

README.md

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+---
+license: mit
+base_model: google/vivit-b-16x2-kinetics400
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: vivit-surf-analytics-runpod
+  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-surf-analytics-runpod
+
+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: 0.7570
+- Accuracy: 0.9023
+- F1: 0.9016
+
+## 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: 1
+- eval_batch_size: 1
+- 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: 741
+
+### Training results
+
+| Training Loss | Epoch   | Step  | Accuracy | F1     | Validation Loss |
+|:-------------:|:-------:|:-----:|:--------:|:------:|:---------------:|
+| 1.3533        | 0.05    | 741   | 0.8393   | 0.8382 | 0.7031          |
+| 0.0028        | 1.05    | 1482  | 0.8482   | 0.8460 | 0.7500          |
+| 0.0021        | 2.05    | 2223  | 0.8839   | 0.8821 | 0.5604          |
+| 0.0002        | 3.05    | 2964  | 0.9018   | 0.9001 | 0.3880          |
+| 0.0001        | 4.05    | 3705  | 0.9286   | 0.9284 | 0.4309          |
+| 0.0001        | 5.05    | 4446  | 0.9107   | 0.9105 | 0.7365          |
+| 0.8987        | 6.05    | 5187  | 0.8393   | 0.8294 | 0.9310          |
+| 0.4888        | 7.05    | 5928  | 0.875    | 0.8703 | 0.8563          |
+| 0.0001        | 8.05    | 6669  | 0.8929   | 0.8894 | 0.6909          |
+| 0.0018        | 9.05    | 7410  | 0.8929   | 0.8917 | 0.9169          |
+| 0.0           | 10.05   | 8151  | 0.8929   | 0.8928 | 0.6104          |
+| 0.0           | 11.05   | 8892  | 0.9196   | 0.9207 | 0.6125          |
+| 0.0           | 12.05   | 9633  | 0.9286   | 0.9281 | 0.5644          |
+| 0.0           | 13.05   | 10374 | 0.9286   | 0.9286 | 0.5062          |
+| 0.0           | 14.05   | 11115 | 0.9375   | 0.9373 | 0.5186          |
+| 0.0           | 15.0013 | 11116 | 0.7569   | 0.9023 | 0.9016          |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.1+cu121
+- Datasets 2.19.2
+- Tokenizers 0.19.1

all_results.json

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+{
+    "epoch": 15.001349527665317,
+    "eval_accuracy": 0.9023255813953488,
+    "eval_f1": 0.9016146713373171,
+    "eval_loss": 0.756963849067688,
+    "eval_runtime": 137.6677,
+    "eval_samples_per_second": 1.562,
+    "eval_steps_per_second": 1.562
+}

model.safetensors

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 version https://git-lfs.github.com/spec/v1
-oid sha256:1b8c579090f83791c8580d738ddefca55943140575a979eac2e7454db9c39be5
+oid sha256:390070465f1a756a496a70b7ce621e289c5d5b8a847247f983f1d434c37dcc9e
 size 354621528

test_results.json

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+{
+    "epoch": 15.001349527665317,
+    "eval_accuracy": 0.9375,
+    "eval_f1": 0.9373365167161658,
+    "eval_loss": 0.5185860991477966,
+    "eval_runtime": 72.3734,
+    "eval_samples_per_second": 1.548,
+    "eval_steps_per_second": 1.548
+}

val_results.json

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+{
+    "epoch": 15.001349527665317,
+    "eval_accuracy": 0.9023255813953488,
+    "eval_f1": 0.9016146713373171,
+    "eval_loss": 0.756963849067688,
+    "eval_runtime": 137.6677,
+    "eval_samples_per_second": 1.562,
+    "eval_steps_per_second": 1.562
+}