transformers tensorboard safetensors bart text2text-generation generated_from_trainer base_model:checkpoint_global_step_200000 autotrain_compatible endpoints_compatible region:us
---
base_model: checkpoint_global_step_200000
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: fine-tuned-BioBARTv2-20-epochs-1024-input-256-output
  results: []
---

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# fine-tuned-BioBARTv2-20-epochs-1024-input-256-output

This model is a fine-tuned version of [checkpoint_global_step_200000](https://huggingface.co/checkpoint_global_step_200000) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9612
- Rouge1: 0.2101
- Rouge2: 0.0415
- Rougel: 0.1705
- Rougelsum: 0.1695
- Gen Len: 40.3

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 151  | 6.4708          | 0.1075 | 0.0008 | 0.079  | 0.0796    | 69.35   |
| No log        | 2.0   | 302  | 1.1525          | 0.1053 | 0.0308 | 0.0902 | 0.0909    | 22.16   |
| No log        | 3.0   | 453  | 0.9813          | 0.02   | 0.0    | 0.02   | 0.02      | 8.0     |
| 4.2222        | 4.0   | 604  | 0.9282          | 0.1047 | 0.0244 | 0.0791 | 0.0779    | 27.31   |
| 4.2222        | 5.0   | 755  | 0.8997          | 0.166  | 0.0316 | 0.1257 | 0.1248    | 73.57   |
| 4.2222        | 6.0   | 906  | 0.8912          | 0.1626 | 0.0288 | 0.1342 | 0.1327    | 37.82   |
| 0.7695        | 7.0   | 1057 | 0.8761          | 0.1756 | 0.0396 | 0.1377 | 0.1384    | 39.43   |
| 0.7695        | 8.0   | 1208 | 0.8787          | 0.155  | 0.0292 | 0.1225 | 0.1237    | 33.5    |
| 0.7695        | 9.0   | 1359 | 0.8834          | 0.1538 | 0.0268 | 0.1286 | 0.1276    | 27.75   |
| 0.5376        | 10.0  | 1510 | 0.8855          | 0.1924 | 0.0376 | 0.1542 | 0.1533    | 36.22   |
| 0.5376        | 11.0  | 1661 | 0.8915          | 0.1997 | 0.037  | 0.1607 | 0.1611    | 41.79   |
| 0.5376        | 12.0  | 1812 | 0.9022          | 0.1907 | 0.0289 | 0.1517 | 0.1533    | 43.94   |
| 0.5376        | 13.0  | 1963 | 0.9101          | 0.2054 | 0.0412 | 0.1603 | 0.1598    | 45.65   |
| 0.3808        | 14.0  | 2114 | 0.9172          | 0.1905 | 0.0405 | 0.1436 | 0.1441    | 44.98   |
| 0.3808        | 15.0  | 2265 | 0.9382          | 0.2121 | 0.0499 | 0.1729 | 0.1745    | 38.68   |
| 0.3808        | 16.0  | 2416 | 0.9437          | 0.1875 | 0.0387 | 0.1483 | 0.1482    | 37.93   |
| 0.2761        | 17.0  | 2567 | 0.9466          | 0.1935 | 0.0393 | 0.1513 | 0.1513    | 42.51   |
| 0.2761        | 18.0  | 2718 | 0.9518          | 0.2102 | 0.0478 | 0.1651 | 0.1664    | 40.2    |
| 0.2761        | 19.0  | 2869 | 0.9603          | 0.2074 | 0.0396 | 0.1691 | 0.1686    | 37.55   |
| 0.2257        | 20.0  | 3020 | 0.9612          | 0.2101 | 0.0415 | 0.1705 | 0.1695    | 40.3    |


### Framework versions

- Transformers 4.36.2
- Pytorch 1.12.1+cu113
- Datasets 2.16.1
- Tokenizers 0.15.1
