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BEE-spoke-data/roberta-base-description2genre
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2130
- F1: 0.6717
Model description
This classifies one or more genre labels in a multi-label setting for a given book description.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 4e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-10
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.04
- num_epochs: 6.0
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.3118 | 1.0 | 62 | 0.2885 | 0.3362 |
| 0.2676 | 2.0 | 124 | 0.2511 | 0.4882 |
| 0.2325 | 3.0 | 186 | 0.2272 | 0.6093 |
| 0.2127 | 4.0 | 248 | 0.2181 | 0.6591 |
| 0.1978 | 5.0 | 310 | 0.2140 | 0.6686 |
| 0.1817 | 6.0 | 372 | 0.2130 | 0.6717 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.2.0.dev20231001+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
