File size: 1,846 Bytes
601a4f2 16fe5db 601a4f2 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 |
---
license: mit
tags:
- generated_from_trainer
metrics:
- rouge
base_model: facebook/bart-large-cnn
model-index:
- name: bart-large-cnn_summarizer_30216
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. -->
# bart-large-cnn_summarizer_30216
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co./facebook/bart-large-cnn) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9800
- Rouge1: 51.6258
- Rouge2: 33.4629
- Rougel: 40.3034
- Rougelsum: 47.8482
- Gen Len: 105.0622
## 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: 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: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| 0.8653 | 1.0 | 12086 | 0.9274 | 51.1144 | 32.972 | 39.8981 | 47.2905 | 100.2417 |
| 0.6741 | 2.0 | 24172 | 0.9330 | 51.5965 | 33.5021 | 40.4048 | 47.8046 | 103.9732 |
| 0.4802 | 3.0 | 36258 | 0.9800 | 51.6258 | 33.4629 | 40.3034 | 47.8482 | 105.0622 |
### Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1
|