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-352-output
  results: []
---

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# fine-tuned-BioBARTv2-20-epochs-1024-input-352-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: 0.7137
- Rouge1: 0.1879
- Rouge2: 0.0399
- Rougel: 0.1477
- Rougelsum: 0.1473
- Gen Len: 37.71

## 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  | 6.2824          | 0.0873 | 0.0004 | 0.0696 | 0.0699    | 59.17   |
| No log        | 2.0   | 302  | 0.8585          | 0.1021 | 0.0276 | 0.0905 | 0.0905    | 23.51   |
| No log        | 3.0   | 453  | 0.7401          | 0.0672 | 0.0142 | 0.0529 | 0.0523    | 21.97   |
| 4.0066        | 4.0   | 604  | 0.6962          | 0.1224 | 0.0287 | 0.0968 | 0.0968    | 29.25   |
| 4.0066        | 5.0   | 755  | 0.6739          | 0.1497 | 0.0295 | 0.1199 | 0.1188    | 34.66   |
| 4.0066        | 6.0   | 906  | 0.6642          | 0.1548 | 0.0299 | 0.1156 | 0.1142    | 50.23   |
| 0.5957        | 7.0   | 1057 | 0.6592          | 0.1319 | 0.0281 | 0.0993 | 0.0979    | 37.47   |
| 0.5957        | 8.0   | 1208 | 0.6532          | 0.1756 | 0.0366 | 0.1416 | 0.1411    | 38.41   |
| 0.5957        | 9.0   | 1359 | 0.6604          | 0.1636 | 0.034  | 0.1298 | 0.1291    | 33.72   |
| 0.4198        | 10.0  | 1510 | 0.6624          | 0.1841 | 0.0389 | 0.1439 | 0.1423    | 37.58   |
| 0.4198        | 11.0  | 1661 | 0.6656          | 0.1864 | 0.0331 | 0.1479 | 0.1472    | 46.92   |
| 0.4198        | 12.0  | 1812 | 0.6683          | 0.1918 | 0.0426 | 0.1432 | 0.1432    | 45.94   |
| 0.4198        | 13.0  | 1963 | 0.6796          | 0.1851 | 0.0374 | 0.1396 | 0.1393    | 47.93   |
| 0.3012        | 14.0  | 2114 | 0.6847          | 0.1933 | 0.0393 | 0.1413 | 0.1407    | 41.22   |
| 0.3012        | 15.0  | 2265 | 0.6919          | 0.175  | 0.036  | 0.132  | 0.131     | 38.91   |
| 0.3012        | 16.0  | 2416 | 0.7011          | 0.1985 | 0.03   | 0.1495 | 0.1494    | 43.78   |
| 0.2208        | 17.0  | 2567 | 0.7098          | 0.1836 | 0.033  | 0.1395 | 0.1377    | 38.65   |
| 0.2208        | 18.0  | 2718 | 0.7080          | 0.1888 | 0.038  | 0.1433 | 0.1417    | 39.49   |
| 0.2208        | 19.0  | 2869 | 0.7127          | 0.186  | 0.0351 | 0.1479 | 0.1479    | 39.35   |
| 0.1823        | 20.0  | 3020 | 0.7137          | 0.1879 | 0.0399 | 0.1477 | 0.1473    | 37.71   |


### Framework versions

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