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-288-output
  results: []
---

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# fine-tuned-BioBARTv2-20-epochs-1024-input-288-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: 0.8737
- Rouge1: 0.1792
- Rouge2: 0.0323
- Rougel: 0.1391
- Rougelsum: 0.1399
- Gen Len: 36.3

## 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  | 6.4453          | 0.0289 | 0.0003 | 0.0283 | 0.0278    | 21.32   |
| No log        | 2.0   | 302  | 1.0350          | 0.1165 | 0.0335 | 0.0969 | 0.0965    | 34.35   |
| No log        | 3.0   | 453  | 0.8905          | 0.0745 | 0.0151 | 0.0539 | 0.0545    | 32.84   |
| 4.1419        | 4.0   | 604  | 0.8387          | 0.1225 | 0.0334 | 0.0911 | 0.0909    | 31.01   |
| 4.1419        | 5.0   | 755  | 0.8139          | 0.17   | 0.0335 | 0.1343 | 0.1339    | 53.7    |
| 4.1419        | 6.0   | 906  | 0.8070          | 0.1165 | 0.0242 | 0.0936 | 0.0916    | 26.25   |
| 0.7039        | 7.0   | 1057 | 0.7982          | 0.1367 | 0.0299 | 0.0998 | 0.1007    | 43.94   |
| 0.7039        | 8.0   | 1208 | 0.7926          | 0.1689 | 0.0408 | 0.1265 | 0.1276    | 47.35   |
| 0.7039        | 9.0   | 1359 | 0.8005          | 0.1603 | 0.0336 | 0.1338 | 0.1335    | 31.24   |
| 0.4936        | 10.0  | 1510 | 0.8062          | 0.1641 | 0.0358 | 0.1256 | 0.1254    | 33.11   |
| 0.4936        | 11.0  | 1661 | 0.8085          | 0.1934 | 0.0437 | 0.1527 | 0.1542    | 42.14   |
| 0.4936        | 12.0  | 1812 | 0.8143          | 0.1699 | 0.0398 | 0.1304 | 0.1301    | 49.52   |
| 0.4936        | 13.0  | 1963 | 0.8348          | 0.1619 | 0.0272 | 0.1263 | 0.1262    | 31.8    |
| 0.352         | 14.0  | 2114 | 0.8365          | 0.2093 | 0.0485 | 0.1657 | 0.1667    | 42.77   |
| 0.352         | 15.0  | 2265 | 0.8455          | 0.168  | 0.0345 | 0.1298 | 0.131     | 35.95   |
| 0.352         | 16.0  | 2416 | 0.8532          | 0.1953 | 0.048  | 0.1546 | 0.1561    | 37.21   |
| 0.2569        | 17.0  | 2567 | 0.8604          | 0.1834 | 0.0359 | 0.1431 | 0.1442    | 39.24   |
| 0.2569        | 18.0  | 2718 | 0.8702          | 0.1628 | 0.029  | 0.1209 | 0.1217    | 35.94   |
| 0.2569        | 19.0  | 2869 | 0.8712          | 0.1792 | 0.04   | 0.1382 | 0.139     | 37.38   |
| 0.211         | 20.0  | 3020 | 0.8737          | 0.1792 | 0.0323 | 0.1391 | 0.1399    | 36.3    |


### Framework versions

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