| --- |
| license: mit |
| tags: |
| - video-classification |
| - timesformer |
| - action-recognition |
| - hmdb51 |
| - pytorch |
| datasets: |
| - hmdb51 |
| --- |
| |
| # 🎬 TimeSformer Fine-Tuned on HMDB51 |
|
|
| This model is a fine-tuned version of **TimeSformer (Time-Space Transformer)** for **video action recognition**, trained on the **HMDB51 dataset**. |
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| --- |
|
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| ## 📌 Model Overview |
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|
| - **Architecture:** TimeSformer (Transformer-based video model) |
| - **Task:** Video Classification / Action Recognition |
| - **Dataset:** HMDB51 (51 human action classes) |
| - **Framework:** PyTorch + Hugging Face Transformers |
| - **Training Device:** CUDA (GPU) |
|
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| This model learns spatial and temporal features from video frames using transformer-based attention mechanisms. |
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| --- |
|
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| ## 📊 Training Details |
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|
| - **Epochs:** 15 |
| - **Training Strategy:** |
| - Mixed Precision Training (`torch.cuda.amp`) |
| - Early stopping based on validation performance |
| - Best model checkpoint saved during training |
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|
| --- |
|
|
| ## 📈 Training Results |
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|
| | Epoch | Train Loss | Train Accuracy | Val Loss | Val Accuracy | |
| |------|------------|----------------|----------|--------------| |
| | 1 | 3.9314 | 0.0323 | 3.7800 | 0.1248 | |
| | 2 | 3.5892 | 0.1976 | 3.2530 | 0.4353 | |
| | 3 | 3.0235 | 0.4354 | 2.6567 | 0.5340 | |
| | 4 | 2.5720 | 0.5246 | 2.2347 | 0.6033 | |
| | 5 | 2.2836 | 0.6009 | 2.0135 | 0.6327 | |
| | 6 | 2.0897 | 0.6419 | 1.8659 | 0.6536 | |
| | 7 | 1.9678 | 0.6807 | 1.8017 | 0.6667 | |
| | 8 | 1.8847 | 0.7030 | 1.7705 | 0.6627 | |
| | 9 | 1.8213 | 0.7237 | 1.7355 | 0.6627 | |
| | 10 | 1.7576 | 0.7414 | 1.7340 | 0.6680 | |
| | 11 | 1.7098 | 0.7549 | 1.7234 | 0.6765 | |
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|
| ### ✅ Best Validation Accuracy: **67.65%** |
| - Achieved at **Epoch 11** |
| - Model checkpoint saved automatically |
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|
| --- |
|
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| ## 🧠 Dataset |
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| **HMDB51** is a widely used human action recognition dataset: |
| - 51 action classes |
| - Real-world videos |
| - Diverse motion patterns and scenes |
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|
| --- |
|
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| ## 🚀 Usage |
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|
| ### Install Dependencies |
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|
| ```bash |
| pip install torch torchvision transformers |
