metadata
library_name: transformers
license: apache-2.0
base_model: allenai/led-base-16384
tags:
- generated_from_trainer
datasets:
- scientific_lay_summarisation
model-index:
- name: led_summarizer
results: []
led_summarizer
This model is a fine-tuned version of allenai/led-base-16384 on the scientific_lay_summarisation dataset. It achieves the following results on the evaluation set:
- Loss: 2.6657
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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.2606 | 0.1067 | 10 | 3.0145 |
| 3.1127 | 0.2133 | 20 | 2.8998 |
| 2.9749 | 0.32 | 30 | 2.8432 |
| 2.9502 | 0.4267 | 40 | 2.7848 |
| 2.8664 | 0.5333 | 50 | 2.7457 |
| 2.8505 | 0.64 | 60 | 2.7244 |
| 2.7979 | 0.7467 | 70 | 2.6993 |
| 2.778 | 0.8533 | 80 | 2.6769 |
| 2.7792 | 0.96 | 90 | 2.6657 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1