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--- |
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license: apache-2.0 |
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base_model: albert-xxlarge-v2 |
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tags: |
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- genre |
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- books |
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- multi-label |
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- dataset tools |
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metrics: |
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- f1 |
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widget: |
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- text: >- |
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Meet Gertrude, a penguin detective who can't stand the cold. When a shrimp |
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cocktail goes missing from the Iceberg Lounge, it's up to her to solve the |
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mystery, wearing her collection of custom-made tropical turtlenecks. |
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example_title: Tropical Turtlenecks |
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- text: >- |
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Professor Wobblebottom, a notorious forgetful scientist, invents a time |
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machine but forgets how to use it. Now he is randomly popping into |
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significant historical events, ruining everything. The future of the past is |
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in the balance. |
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example_title: When I Forgot The Time |
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- text: >- |
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In a world where hugs are currency and your social credit score is |
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determined by your knack for dad jokes, John, a man who is allergic to |
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laughter, has to navigate his way without becoming broke—or broken-hearted. |
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example_title: Laugh Now, Pay Later |
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- text: >- |
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Emily, a vegan vampire, is faced with an ethical dilemma when she falls head |
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over heels for a human butcher named Bob. Will she bite the forbidden fruit |
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or stick to her plant-based blood substitutes? |
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example_title: Love at First Bite... Or Not |
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- text: >- |
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Steve, a sentient self-driving car, wants to be a Broadway star. His dream |
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seems unreachable until he meets Sally, a GPS system with the voice of an |
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angel and ambitions of her own. |
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example_title: Broadway or Bust |
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- text: >- |
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Dr. Fredrick Tensor, a socially awkward computer scientist, is on a quest to |
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perfect AI companionship. However, his models keep outputting cringe-worthy, |
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melodramatic waifus that scare away even the most die-hard fans of AI |
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romance. Frustrated and lonely, Fredrick must debug his love life and |
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algorithms before it's too late. |
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example_title: Love.exe Has Stopped Working |
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language: |
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- en |
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pipeline_tag: text-classification |
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--- |
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# albert-xxlarge-v2-description2genre |
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This model is a fine-tuned version of [albert-xxlarge-v2](https://huggingface.co/albert-xxlarge-v2) for multi-label classification with 18 labels. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1905 |
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- F1: 0.7058 |
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## Usage |
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```python |
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# pip install -q transformers accelerate optimum |
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from transformers import pipeline |
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pipe = pipeline( |
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"text-classification", |
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model="BEE-spoke-data/albert-xxlarge-v2-description2genre" |
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) |
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pipe.model = pipe.model.to_bettertransformer() |
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description = "On the Road is a 1957 novel by American writer Jack Kerouac, based on the travels of Kerouac and his friends across the United States. It is considered a defining work of the postwar Beat and Counterculture generations, with its protagonists living life against a backdrop of jazz, poetry, and drug use." # @param {type:"string"} |
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result = pipe(description, return_all_scores=True)[0] |
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print(result) |
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``` |
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> usage of BetterTransformer (via `optimum`) is optional, but recommended unless you enjoy waiting. |
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## Model description |
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This classifies one or more **genre** labels in a **multi-label** setting for a given book **description**. |
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The 'standard' way of interpreting the predictions is that the predicted labels for a given example are **only the ones with a greater than 50% probability.** |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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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- num_epochs: 5.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 0.2903 | 0.99 | 123 | 0.2686 | 0.4011 | |
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| 0.2171 | 2.0 | 247 | 0.2168 | 0.6493 | |
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| 0.1879 | 3.0 | 371 | 0.1990 | 0.6612 | |
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| 0.1476 | 4.0 | 495 | 0.1879 | 0.7060 | |
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| 0.1279 | 4.97 | 615 | 0.1905 | 0.7058 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.2.0.dev20231001+cu121 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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