Model save

README.md

@@ -21,11 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 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: 2.9041
-- Accuracy: 0.5333
-- Precision: 0.2844
-- Recall: 0.5333
-- F1: 0.3710
+- Loss: 0.5625
+- Accuracy: 0.7273
+- Precision: 0.8295
+- Recall: 0.7273
+- F1: 0.7133
 
 ## Model description
 
@@ -51,17 +51,17 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- training_steps: 1275
+- training_steps: 1280
 
 ### Training results
 
 | Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
 |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
-| 0.5269        | 1.0    | 256  | 0.6199          | 0.6667   | 0.7949    | 0.6667 | 0.6138 |
-| 0.3915        | 2.0    | 512  | 2.0730          | 0.5333   | 0.2844    | 0.5333 | 0.3710 |
-| 0.1333        | 3.0    | 768  | 3.0172          | 0.5333   | 0.2844    | 0.5333 | 0.3710 |
-| 0.054         | 4.0    | 1024 | 2.9344          | 0.5333   | 0.2844    | 0.5333 | 0.3710 |
-| 0.0004        | 4.9805 | 1275 | 2.9041          | 0.5333   | 0.2844    | 0.5333 | 0.3710 |
+| 0.5739        | 1.0    | 257  | 0.2189          | 1.0      | 1.0       | 1.0    | 1.0    |
+| 0.3031        | 2.0    | 514  | 0.1917          | 0.9091   | 0.9242    | 0.9091 | 0.9091 |
+| 0.1346        | 3.0    | 771  | 1.5586          | 0.6364   | 0.7980    | 0.6364 | 0.5974 |
+| 0.0861        | 4.0    | 1028 | 0.6874          | 0.7273   | 0.8295    | 0.7273 | 0.7133 |
+| 0.0005        | 4.9805 | 1280 | 0.5625          | 0.7273   | 0.8295    | 0.7273 | 0.7133 |
 
 
 ### Framework versions

model.safetensors

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 size 344937368

runs/Sep26_11-58-23_hmudgx/events.out.tfevents.1727341107.hmudgx.658204.6

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