File size: 1,927 Bytes
56a7189 1c9d44f 56a7189 cca6399 56a7189 cca6399 56a7189 cca6399 56a7189 |
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 |
---
tags:
- generated_from_trainer
metrics:
- rouge
base_model: fnlp/bart-large-chinese
model-index:
- name: bart-large-chinese-cnhdwriter
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-chinese-cnhdwriter
This model is a fine-tuned version of [fnlp/bart-large-chinese](https://huggingface.co/fnlp/bart-large-chinese) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3859
- Rouge1: 16.8496
- Rouge2: 2.5548
- Rougel: 16.8123
- Rougelsum: 16.8056
- Gen Len: 18.9357
## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:------:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 1.2119 | 1.0 | 62716 | 1.1876 | 15.3858 | 2.1251 | 15.3709 | 15.3705 | 18.7269 |
| 1.0847 | 2.0 | 125432 | 1.3353 | 13.7743 | 1.9047 | 13.7664 | 13.7421 | 18.6183 |
| 0.6995 | 3.0 | 188148 | 1.2209 | 16.6797 | 2.3979 | 16.6258 | 16.6368 | 18.8953 |
| 0.4819 | 4.0 | 250864 | 1.3859 | 16.8496 | 2.5548 | 16.8123 | 16.8056 | 18.9357 |
### Framework versions
- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.17.0
- Tokenizers 0.10.3
|