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Graziela
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videomae-base-finetuned-ucf101-subset

Video Classification
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videomae
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End of training

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Files changed (8) hide show
  1. README.md +12 -14
  2. config.json +1 -1
  3. model.safetensors +1 -1
  4. runs/Sep12_21-15-57_d4aa18986218/events.out.tfevents.1726175768.d4aa18986218.908.0 +3 -0
  5. runs/Sep12_21-42-00_d4aa18986218/events.out.tfevents.1726177331.d4aa18986218.2331.0 +3 -0
  6. runs/Sep12_21-44-52_d4aa18986218/events.out.tfevents.1726177504.d4aa18986218.2331.1 +3 -0
  7. runs/Sep12_21-47-44_d4aa18986218/events.out.tfevents.1726177666.d4aa18986218.2331.2 +3 -0
  8. training_args.bin +2 -2
README.md CHANGED
@@ -1,4 +1,5 @@
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  ---
 
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  license: cc-by-nc-4.0
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  base_model: MCG-NJU/videomae-base
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  tags:
@@ -17,8 +18,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6580
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- - Accuracy: 0.7857
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  ## Model description
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@@ -38,27 +39,24 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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- - train_batch_size: 8
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- - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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- - training_steps: 148
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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- |:-------------:|:------:|:----:|:---------------:|:--------:|
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- | 2.1042 | 0.2568 | 38 | 1.9322 | 0.3714 |
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- | 1.1133 | 1.2568 | 76 | 1.1493 | 0.4429 |
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- | 0.5362 | 2.2568 | 114 | 0.8444 | 0.6857 |
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- | 0.3334 | 3.2297 | 148 | 0.6580 | 0.7857 |
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  ### Framework versions
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- - Transformers 4.42.4
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- - Pytorch 2.3.1+cu121
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- - Datasets 2.20.0
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  - Tokenizers 0.19.1
 
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  ---
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+ library_name: transformers
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  license: cc-by-nc-4.0
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  base_model: MCG-NJU/videomae-base
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  tags:
 
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  This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.2985
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+ - Accuracy: 0.4143
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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+ - train_batch_size: 1
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+ - eval_batch_size: 1
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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+ - training_steps: 300
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.3254 | 1.0 | 300 | 1.2985 | 0.4143 |
 
 
 
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  ### Framework versions
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+ - Transformers 4.44.2
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+ - Pytorch 1.12.0+cu102
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+ - Datasets 3.0.0
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  - Tokenizers 0.19.1
config.json CHANGED
@@ -49,7 +49,7 @@
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  "problem_type": "single_label_classification",
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  "qkv_bias": true,
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  "torch_dtype": "float32",
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- "transformers_version": "4.42.4",
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  "tubelet_size": 2,
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  "use_mean_pooling": false
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  }
 
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  "problem_type": "single_label_classification",
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  "qkv_bias": true,
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  "torch_dtype": "float32",
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+ "transformers_version": "4.44.2",
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  "tubelet_size": 2,
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  "use_mean_pooling": false
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  }
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