Summarization-Bloom-560m
This model is a fine-tuned version of bigscience/bloom-560m on the scitldr dataset. It achieves the following results on the evaluation set:
- Loss: 2.8578
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.8487 | 0.2510 | 500 | 2.9019 |
| 2.8069 | 0.5020 | 1000 | 2.8799 |
| 2.8195 | 0.7530 | 1500 | 2.8660 |
| 2.8024 | 1.0040 | 2000 | 2.8556 |
| 2.661 | 1.2550 | 2500 | 2.8637 |
| 2.6136 | 1.5060 | 3000 | 2.8608 |
| 2.5816 | 1.7570 | 3500 | 2.8578 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for pkbiswas/Bloom-560m-Summarization-QLoRa
Base model
bigscience/bloom-560m