---
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: checkpoint-6500-finetuned2-2010-2016
  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. -->

# checkpoint-6500-finetuned2-2010-2016

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Rouge1: 1.0
- Rouge2: 0.96
- Rougel: 1.0
- Rougelsum: 1.0
- Gen Len: 6.4

## 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: 0.0003
- train_batch_size: 32
- eval_batch_size: 32
- seed: 1
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 22   | 0.5473          | 0.2919 | 0.2095 | 0.2929 | 0.29      | 6.11    |
| No log        | 2.0   | 44   | 0.3837          | 0.3426 | 0.2692 | 0.3434 | 0.3433    | 6.2     |
| No log        | 3.0   | 66   | 0.2416          | 0.5336 | 0.4842 | 0.532  | 0.533     | 6.25    |
| No log        | 4.0   | 88   | 0.1266          | 0.7338 | 0.6501 | 0.7334 | 0.7306    | 6.28    |
| 0.6352        | 5.0   | 110  | 0.0454          | 0.8998 | 0.8382 | 0.9002 | 0.899     | 6.26    |
| 0.6352        | 6.0   | 132  | 0.0125          | 0.9864 | 0.9423 | 0.9864 | 0.9868    | 6.39    |
| 0.6352        | 7.0   | 154  | 0.0029          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.6352        | 8.0   | 176  | 0.0011          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.6352        | 9.0   | 198  | 0.0013          | 0.9922 | 0.95   | 0.9922 | 0.9922    | 6.43    |
| 0.0586        | 10.0  | 220  | 0.0067          | 0.995  | 0.95   | 0.995  | 0.995     | 6.4     |
| 0.0586        | 11.0  | 242  | 0.0004          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0586        | 12.0  | 264  | 0.0002          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0586        | 13.0  | 286  | 0.0142          | 0.9983 | 0.956  | 0.9983 | 0.9983    | 6.43    |
| 0.0149        | 14.0  | 308  | 0.0001          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0149        | 15.0  | 330  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0149        | 16.0  | 352  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0149        | 17.0  | 374  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0149        | 18.0  | 396  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0064        | 19.0  | 418  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0064        | 20.0  | 440  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0064        | 21.0  | 462  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0064        | 22.0  | 484  | 0.0002          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0048        | 23.0  | 506  | 0.0003          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0048        | 24.0  | 528  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0048        | 25.0  | 550  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0048        | 26.0  | 572  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0048        | 27.0  | 594  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0032        | 28.0  | 616  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0032        | 29.0  | 638  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0032        | 30.0  | 660  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0032        | 31.0  | 682  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0016        | 32.0  | 704  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0016        | 33.0  | 726  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0016        | 34.0  | 748  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0016        | 35.0  | 770  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0016        | 36.0  | 792  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0019        | 37.0  | 814  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0019        | 38.0  | 836  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0019        | 39.0  | 858  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0019        | 40.0  | 880  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0014        | 41.0  | 902  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0014        | 42.0  | 924  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0014        | 43.0  | 946  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0014        | 44.0  | 968  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0014        | 45.0  | 990  | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0013        | 46.0  | 1012 | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0013        | 47.0  | 1034 | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0013        | 48.0  | 1056 | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0013        | 49.0  | 1078 | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |
| 0.0011        | 50.0  | 1100 | 0.0000          | 1.0    | 0.96   | 1.0    | 1.0       | 6.4     |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.0.1
- Datasets 2.14.6
- Tokenizers 0.14.1