metadata
license: apache-2.0
base_model: allenai/led-base-16384
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: LED-Base-NSPCC
results: []
LED-Base-NSPCC
This model is a fine-tuned version of allenai/led-base-16384 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.8734
- Rouge1: 0.4910
- Rouge2: 0.2207
- Rougel: 0.2847
- Rougelsum: 0.2840
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: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 2.4662 | 0.9947 | 47 | 1.9451 | 0.4528 | 0.1809 | 0.2560 | 0.2558 |
| 1.6508 | 1.9894 | 94 | 1.8497 | 0.4889 | 0.2146 | 0.2720 | 0.2716 |
| 1.2549 | 2.9841 | 141 | 1.8268 | 0.4812 | 0.2092 | 0.2756 | 0.2753 |
| 0.9955 | 3.9788 | 188 | 1.8734 | 0.4910 | 0.2207 | 0.2847 | 0.2840 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1