|
--- |
|
license: apache-2.0 |
|
base_model: allenai/led-base-16384 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: led_large_16384_docstring |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# led_large_16384_docstring |
|
|
|
This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.4572 |
|
- Rouge2 Precision: 0.091 |
|
- Rouge2 Recall: 0.2244 |
|
- Rouge2 Fmeasure: 0.1219 |
|
|
|
## 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: 2 |
|
- eval_batch_size: 2 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 8 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 1500 |
|
- num_epochs: 3.0 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | |
|
|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:| |
|
| 1.099 | 1.33 | 5000 | 1.5197 | 0.0898 | 0.22 | 0.1202 | |
|
| 0.9149 | 2.67 | 10000 | 1.4572 | 0.091 | 0.2244 | 0.1219 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.39.2 |
|
- Pytorch 2.1.2+cu121 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.15.2 |
|
|
