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-192-output
  results: []
---

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# fine-tuned-BioBARTv2-20-epochs-1024-input-192-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: 1.2139
- Rouge1: 0.1795
- Rouge2: 0.0354
- Rougel: 0.1282
- Rougelsum: 0.1304
- Gen Len: 38.23

## 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  | 6.6012          | 0.0046 | 0.0001 | 0.0045 | 0.0046    | 8.77    |
| No log        | 2.0   | 302  | 1.4692          | 0.1068 | 0.0318 | 0.0933 | 0.0937    | 29.33   |
| No log        | 3.0   | 453  | 1.2563          | 0.0982 | 0.0232 | 0.0736 | 0.0745    | 36.78   |
| 4.4063        | 4.0   | 604  | 1.1824          | 0.1163 | 0.033  | 0.0884 | 0.0888    | 31.46   |
| 4.4063        | 5.0   | 755  | 1.1451          | 0.1667 | 0.0343 | 0.1302 | 0.1308    | 42.16   |
| 4.4063        | 6.0   | 906  | 1.1288          | 0.1428 | 0.0268 | 0.1118 | 0.1124    | 33.8    |
| 0.9455        | 7.0   | 1057 | 1.1192          | 0.1474 | 0.035  | 0.1089 | 0.1098    | 39.35   |
| 0.9455        | 8.0   | 1208 | 1.1202          | 0.1598 | 0.0354 | 0.1227 | 0.1245    | 37.79   |
| 0.9455        | 9.0   | 1359 | 1.1227          | 0.1683 | 0.0312 | 0.1236 | 0.1247    | 50.05   |
| 0.6533        | 10.0  | 1510 | 1.1241          | 0.1744 | 0.0447 | 0.1341 | 0.1364    | 39.0    |
| 0.6533        | 11.0  | 1661 | 1.1321          | 0.1703 | 0.0411 | 0.1273 | 0.1285    | 42.15   |
| 0.6533        | 12.0  | 1812 | 1.1465          | 0.1756 | 0.0343 | 0.1258 | 0.1277    | 34.42   |
| 0.6533        | 13.0  | 1963 | 1.1560          | 0.1854 | 0.0442 | 0.1381 | 0.14      | 38.38   |
| 0.455         | 14.0  | 2114 | 1.1690          | 0.1913 | 0.0388 | 0.1371 | 0.1398    | 39.29   |
| 0.455         | 15.0  | 2265 | 1.1845          | 0.1688 | 0.0305 | 0.1205 | 0.1226    | 34.5    |
| 0.455         | 16.0  | 2416 | 1.1860          | 0.1913 | 0.039  | 0.1345 | 0.136     | 41.5    |
| 0.3282        | 17.0  | 2567 | 1.1955          | 0.1782 | 0.0344 | 0.1243 | 0.1266    | 43.78   |
| 0.3282        | 18.0  | 2718 | 1.2108          | 0.1796 | 0.0386 | 0.1295 | 0.1319    | 37.64   |
| 0.3282        | 19.0  | 2869 | 1.2160          | 0.1762 | 0.034  | 0.1255 | 0.1277    | 38.08   |
| 0.2642        | 20.0  | 3020 | 1.2139          | 0.1795 | 0.0354 | 0.1282 | 0.1304    | 38.23   |


### Framework versions

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