metadata
license: apache-2.0
base_model: slauw87/bart_summarisation
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart_summarisation
results: []
bart_summarisation
This model is a fine-tuned version of slauw87/bart_summarisation on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.9189
- Rouge1: 0.3009
- Rouge2: 0.1043
- Rougel: 0.211
- Rougelsum: 0.2108
- Gen Len: 67.473
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: 2e-05
- train_batch_size: 16
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 313 | 1.8971 | 0.2972 | 0.1024 | 0.2092 | 0.209 | 67.394 |
| 2.2319 | 2.0 | 626 | 1.9189 | 0.3009 | 0.1043 | 0.211 | 0.2108 | 67.473 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cpu
- Datasets 2.15.0
- Tokenizers 0.15.0