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---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-base-ckb
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-base-ckb
This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co./facebook/bart-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6353
- Rouge1: 0.0
- Rouge2: 0.0
- Rougel: 0.0
- Rougelsum: 0.0
- Cer: 4.7349
- Gen Len: 13.2035
## 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: 320
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
### Training results
| Training Loss | Epoch | Step | Cer | Gen Len | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:-------:|:-------:|:---------------:|:------:|:------:|:------:|:---------:|
| 3.5765 | 0.11 | 500 | 10.3648 | 16.358 | 3.4338 | 0.0 | 0.0 | 0.0 | 0.0 |
| 3.1749 | 0.22 | 1000 | 10.955 | 15.828 | 3.0110 | 0.0 | 0.0 | 0.0 | 0.0 |
| 2.8696 | 0.33 | 1500 | 11.2579 | 15.358 | 2.6943 | 0.0 | 0.0 | 0.0 | 0.0 |
| 2.6279 | 0.43 | 2000 | 11.6734 | 14.8565 | 2.4300 | 0.0 | 0.0 | 0.0 | 0.0 |
| 2.4166 | 0.54 | 2500 | 11.028 | 14.523 | 2.2248 | 0.0 | 0.0 | 0.0 | 0.0 |
| 2.2444 | 0.65 | 3000 | 10.4379 | 14.4185 | 2.0490 | 0.0 | 0.0 | 0.0 | 0.0 |
| 2.0902 | 0.76 | 3500 | 10.0905 | 14.242 | 1.8756 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.9565 | 0.87 | 4000 | 9.7629 | 14.042 | 1.7377 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.8319 | 0.98 | 4500 | 9.4737 | 13.877 | 1.6244 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.7104 | 1.09 | 5000 | 9.153 | 13.825 | 1.5353 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.6148 | 1.2 | 5500 | 8.8125 | 13.726 | 1.4422 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.5459 | 1.3 | 6000 | 8.5589 | 13.681 | 1.3755 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.4837 | 1.41 | 6500 | 8.2717 | 13.6225 | 1.3035 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.4219 | 1.52 | 7000 | 8.0684 | 13.549 | 1.2407 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.3743 | 1.63 | 7500 | 7.7684 | 13.502 | 1.1865 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.3318 | 1.74 | 8000 | 7.5247 | 13.509 | 1.1503 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.2893 | 1.85 | 8500 | 7.3826 | 13.456 | 1.1085 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.2228 | 2.0 | 9198 | 1.0506 | 0.0 | 0.0 | 0.0 | 0.0 | 7.0411 | 13.3935 |
| 0.9343 | 3.0 | 13797 | 0.7769 | 0.0 | 0.0 | 0.0 | 0.0 | 5.5303 | 13.2935 |
| 0.7915 | 4.0 | 18396 | 0.6663 | 0.0 | 0.0 | 0.0 | 0.0 | 4.8928 | 13.209 |
| 0.7436 | 5.0 | 22995 | 0.6353 | 0.0 | 0.0 | 0.0 | 0.0 | 4.7349 | 13.2035 |
### Framework versions
- Transformers 4.34.0.dev0
- Pytorch 1.13.1
- Datasets 2.14.5
- Tokenizers 0.13.3
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