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-128-output
  results: []
---

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# fine-tuned-BioBARTv2-20-epochs-1024-input-128-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: 1.2302
- Rouge1: 0.167
- Rouge2: 0.028
- Rougel: 0.1281
- Rougelsum: 0.131
- Gen Len: 32.85

## 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  | 6.5693          | 0.0057 | 0.0    | 0.0056 | 0.0056    | 14.45   |
| No log        | 2.0   | 302  | 1.4553          | 0.1129 | 0.0301 | 0.0914 | 0.0905    | 71.9    |
| No log        | 3.0   | 453  | 1.2597          | 0.0826 | 0.0198 | 0.0632 | 0.0633    | 21.95   |
| 4.4001        | 4.0   | 604  | 1.1822          | 0.1232 | 0.0277 | 0.0949 | 0.0935    | 35.83   |
| 4.4001        | 5.0   | 755  | 1.1447          | 0.1804 | 0.0323 | 0.1378 | 0.1389    | 44.16   |
| 4.4001        | 6.0   | 906  | 1.1391          | 0.1413 | 0.0248 | 0.1079 | 0.1099    | 33.3    |
| 0.9475        | 7.0   | 1057 | 1.1235          | 0.1559 | 0.0302 | 0.1215 | 0.122     | 31.81   |
| 0.9475        | 8.0   | 1208 | 1.1208          | 0.1934 | 0.0394 | 0.1574 | 0.1603    | 38.23   |
| 0.9475        | 9.0   | 1359 | 1.1294          | 0.1589 | 0.0318 | 0.123  | 0.1252    | 27.8    |
| 0.6549        | 10.0  | 1510 | 1.1327          | 0.1517 | 0.0336 | 0.1145 | 0.115     | 33.1    |
| 0.6549        | 11.0  | 1661 | 1.1378          | 0.1707 | 0.0335 | 0.1321 | 0.1345    | 36.81   |
| 0.6549        | 12.0  | 1812 | 1.1514          | 0.173  | 0.0355 | 0.1316 | 0.1326    | 41.25   |
| 0.6549        | 13.0  | 1963 | 1.1778          | 0.1484 | 0.0264 | 0.119  | 0.1207    | 26.2    |
| 0.4557        | 14.0  | 2114 | 1.1822          | 0.1683 | 0.033  | 0.1313 | 0.1335    | 31.15   |
| 0.4557        | 15.0  | 2265 | 1.1998          | 0.1524 | 0.0239 | 0.1132 | 0.116     | 29.92   |
| 0.4557        | 16.0  | 2416 | 1.2123          | 0.1797 | 0.0323 | 0.138  | 0.1388    | 34.11   |
| 0.3267        | 17.0  | 2567 | 1.2175          | 0.1602 | 0.0239 | 0.1228 | 0.1243    | 30.26   |
| 0.3267        | 18.0  | 2718 | 1.2218          | 0.1568 | 0.0252 | 0.1189 | 0.1217    | 32.89   |
| 0.3267        | 19.0  | 2869 | 1.2244          | 0.1849 | 0.0327 | 0.1343 | 0.1375    | 37.66   |
| 0.2632        | 20.0  | 3020 | 1.2302          | 0.167  | 0.028  | 0.1281 | 0.131     | 32.85   |


### Framework versions

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