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-160-output
  results: []
---

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# fine-tuned-BioBARTv2-20-epochs-1024-input-160-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: 1.4289
- Rouge1: 0.1951
- Rouge2: 0.0471
- Rougel: 0.1473
- Rougelsum: 0.1452
- Gen Len: 39.25

## 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  | 6.6467          | 0.0363 | 0.0002 | 0.0297 | 0.0295    | 19.55   |
| No log        | 2.0   | 302  | 1.6612          | 0.1267 | 0.0317 | 0.11   | 0.111     | 24.51   |
| No log        | 3.0   | 453  | 1.4393          | 0.0448 | 0.0077 | 0.0372 | 0.0349    | 15.64   |
| 4.5151        | 4.0   | 604  | 1.3648          | 0.1309 | 0.028  | 0.1019 | 0.101     | 30.13   |
| 4.5151        | 5.0   | 755  | 1.3211          | 0.1644 | 0.0365 | 0.1286 | 0.1273    | 56.4    |
| 4.5151        | 6.0   | 906  | 1.3159          | 0.1229 | 0.0234 | 0.0986 | 0.0981    | 29.91   |
| 1.0545        | 7.0   | 1057 | 1.2964          | 0.1601 | 0.0317 | 0.1291 | 0.1283    | 31.4    |
| 1.0545        | 8.0   | 1208 | 1.2933          | 0.1677 | 0.0355 | 0.1259 | 0.1245    | 39.53   |
| 1.0545        | 9.0   | 1359 | 1.3003          | 0.1808 | 0.0416 | 0.1356 | 0.1344    | 39.72   |
| 0.7195        | 10.0  | 1510 | 1.3179          | 0.1751 | 0.0414 | 0.1334 | 0.1327    | 42.87   |
| 0.7195        | 11.0  | 1661 | 1.3323          | 0.1799 | 0.0415 | 0.1385 | 0.1386    | 38.91   |
| 0.7195        | 12.0  | 1812 | 1.3588          | 0.1851 | 0.031  | 0.1467 | 0.1455    | 33.25   |
| 0.7195        | 13.0  | 1963 | 1.3538          | 0.1852 | 0.0435 | 0.1494 | 0.1462    | 36.31   |
| 0.4924        | 14.0  | 2114 | 1.3737          | 0.1779 | 0.0397 | 0.1361 | 0.1361    | 38.17   |
| 0.4924        | 15.0  | 2265 | 1.3735          | 0.1993 | 0.0423 | 0.1441 | 0.1411    | 45.84   |
| 0.4924        | 16.0  | 2416 | 1.3962          | 0.1778 | 0.0403 | 0.1399 | 0.1378    | 33.99   |
| 0.3509        | 17.0  | 2567 | 1.4080          | 0.1667 | 0.0414 | 0.1215 | 0.1188    | 41.35   |
| 0.3509        | 18.0  | 2718 | 1.4148          | 0.1893 | 0.0437 | 0.1437 | 0.1423    | 39.25   |
| 0.3509        | 19.0  | 2869 | 1.4232          | 0.1904 | 0.0417 | 0.1428 | 0.141     | 41.09   |
| 0.2786        | 20.0  | 3020 | 1.4289          | 0.1951 | 0.0471 | 0.1473 | 0.1452    | 39.25   |


### Framework versions

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