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--- |
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license: apache-2.0 |
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tags: |
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- image-classification |
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- vision |
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- cinematography |
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- film |
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datasets: |
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- szymonrucinski/types-of-film-shots |
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metrics: |
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- accuracy |
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base_model: microsoft/beit-large-patch16-512 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# beit-large-patch16-512: types of film shots |
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## Model description |
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This model is a fine-tuned version of [microsoft/beit-large-patch16-512](https://huggingface.co/microsoft/beit-large-patch16-512) on the szymonrucinski/types-of-film-shots dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2335 |
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- Accuracy: 0.6763 |
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## usage |
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```py |
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from transformers import pipeline |
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from PIL import Image |
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import requests |
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pipe = pipeline( |
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"image-classification", |
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model="pszemraj/beit-large-patch16-512-film-shot-classifier", |
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) |
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url = "https://cdn-uploads.huggingface.co/production/uploads/60bccec062080d33f875cd0c/9YqYvv188ZccCMSzuv0KW.png" |
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image = Image.open(requests.get(url, stream=True).raw) |
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result = pipe(image)[0] |
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print(result) |
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``` |
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try some of these: |
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### class labels |
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The dataset contains the following labels: |
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```json |
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"id2label": { |
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"0": "ambiguous", |
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"1": "closeUp", |
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"2": "detail", |
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"3": "extremeLongShot", |
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"4": "fullShot", |
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"5": "longShot", |
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"6": "mediumCloseUp", |
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"7": "mediumShot" |
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}, |
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``` |
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as plaintext: |
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```txt |
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ambiguous, close up, detail, extreme long shot, full shot, long shot, medium close up, medium shot |
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``` |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 4 |
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- seed: 24414 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.05 |
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- num_epochs: 6.0 |
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- mixed_precision_training: Native AMP |
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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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| 1.0435 | 1.0 | 393 | 1.4799 | 0.4892 | |
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| 1.1554 | 2.0 | 786 | 1.4938 | 0.4892 | |
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| 1.5041 | 3.0 | 1179 | 2.1702 | 0.3597 | |
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| 1.0457 | 4.0 | 1572 | 1.5413 | 0.5683 | |
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| 0.3315 | 5.0 | 1965 | 1.0769 | 0.6978 | |
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| 0.2178 | 6.0 | 2358 | 1.2335 | 0.6763 | |
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### Framework versions |
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- Transformers 4.38.0.dev0 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
