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--- |
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license: mit |
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base_model: roberta-base |
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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 |
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is 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 |
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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 |
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head over heels for a human butcher named Bob. Will she bite the forbidden |
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fruit 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 |
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to perfect AI companionship. However, his models keep outputting |
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cringe-worthy, melodramatic waifus that scare away even the most die-hard |
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fans of AI romance. Frustrated and lonely, Fredrick must debug his love |
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life and 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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<!-- 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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# BEE-spoke-data/roberta-base-description2genre |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2130 |
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- F1: 0.6717 |
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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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## 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: 4e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-10 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.04 |
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- num_epochs: 6.0 |
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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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| 0.3118 | 1.0 | 62 | 0.2885 | 0.3362 | |
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| 0.2676 | 2.0 | 124 | 0.2511 | 0.4882 | |
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| 0.2325 | 3.0 | 186 | 0.2272 | 0.6093 | |
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| 0.2127 | 4.0 | 248 | 0.2181 | 0.6591 | |
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| 0.1978 | 5.0 | 310 | 0.2140 | 0.6686 | |
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| 0.1817 | 6.0 | 372 | 0.2130 | 0.6717 | |
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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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