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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- multi_news
model-index:
- name: summarise_v4
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. -->
# summarise_v4
This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the multi_news dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5264
- Rouge2 Precision: 0.1349
- Rouge2 Recall: 0.1187
- Rouge2 Fmeasure: 0.1227
## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 2.9616 | 0.08 | 10 | 2.8008 | 0.0552 | 0.1944 | 0.0844 |
| 2.7112 | 0.16 | 20 | 2.7017 | 0.1099 | 0.1212 | 0.1078 |
| 2.6842 | 0.24 | 30 | 2.6653 | 0.119 | 0.1252 | 0.1157 |
| 2.4638 | 0.32 | 40 | 2.6306 | 0.1386 | 0.1153 | 0.1222 |
| 2.646 | 0.4 | 50 | 2.6099 | 0.1449 | 0.1095 | 0.122 |
| 2.5128 | 0.48 | 60 | 2.5945 | 0.1259 | 0.1484 | 0.1313 |
| 2.6737 | 0.56 | 70 | 2.5832 | 0.1192 | 0.1252 | 0.118 |
| 2.614 | 0.64 | 80 | 2.5616 | 0.1288 | 0.1179 | 0.1193 |
| 2.4643 | 0.72 | 90 | 2.5612 | 0.1371 | 0.1227 | 0.124 |
| 2.3164 | 0.8 | 100 | 2.5606 | 0.1372 | 0.1177 | 0.1223 |
| 2.4514 | 0.88 | 110 | 2.5339 | 0.1412 | 0.1276 | 0.128 |
| 2.8113 | 0.96 | 120 | 2.5264 | 0.1349 | 0.1187 | 0.1227 |
### Framework versions
- Transformers 4.21.3
- Pytorch 1.12.1+cu113
- Datasets 2.6.2.dev0
- Tokenizers 0.12.1
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