File size: 1,849 Bytes
a56ca09 882f97e a56ca09 882f97e a56ca09 882f97e a56ca09 882f97e a56ca09 882f97e a56ca09 |
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
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: Big-Bart-BBC
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. -->
# Big-Bart-BBC
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co./facebook/bart-large-cnn) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 4.1339
- Rouge1: 0.2638
- Rouge2: 0.1052
- Rougel: 0.2019
- Rougelsum: 0.202
## 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: 5.6e-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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 3.001 | 1.0 | 1652 | 2.8616 | 0.2179 | 0.0571 | 0.1565 | 0.1564 |
| 1.7636 | 2.0 | 3304 | 2.7371 | 0.2423 | 0.0772 | 0.1766 | 0.1767 |
| 0.9422 | 3.0 | 4956 | 3.1619 | 0.2463 | 0.0842 | 0.1832 | 0.1832 |
| 0.4259 | 4.0 | 6608 | 3.5730 | 0.2645 | 0.1009 | 0.2001 | 0.2002 |
| 0.1637 | 5.0 | 8260 | 4.1339 | 0.2638 | 0.1052 | 0.2019 | 0.202 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
|