End of training

README.md

@@ -4,8 +4,6 @@ license: cc-by-nc-4.0
 base_model: MCG-NJU/videomae-base
 tags:
 - generated_from_trainer
-metrics:
-- accuracy
 model-index:
 - name: videomae-base-finetuned-ucf101-subset
   results: []
@@ -17,9 +15,6 @@ should probably proofread and complete it, then remove this comment. -->
 # videomae-base-finetuned-ucf101-subset
 
 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: 1.1055
-- Accuracy: 0.7239
 
 ## Model description
 
@@ -38,28 +33,18 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 5e-05
-- train_batch_size: 2
-- eval_batch_size: 2
+- 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: 9248
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.5676        | 0.25  | 2312 | 1.7078          | 0.4554   |
-| 0.9578        | 1.25  | 4624 | 1.4415          | 0.5283   |
-| 0.9707        | 2.25  | 6936 | 1.4134          | 0.6203   |
-| 0.3863        | 3.25  | 9248 | 1.1055          | 0.7239   |
-
+- training_steps: 57800
 
 ### Framework versions
 
 - Transformers 4.46.3
-- Pytorch 2.5.1+cu118
+- Pytorch 1.11.0+cu102
 - Datasets 3.1.0
 - Tokenizers 0.20.3

config.json

@@ -58,7 +58,6 @@
   "num_frames": 16,
   "num_hidden_layers": 12,
   "patch_size": 16,
-  "problem_type": "single_label_classification",
   "qkv_bias": true,
   "torch_dtype": "float32",
   "transformers_version": "4.46.3",

model.safetensors

@@ -1,3 +1,3 @@
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 size 344980440

training_args.bin

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