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-BioBART-20-epochs-1048-output
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# fine-tuned-BioBART-20-epochs-1048-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: 0.2283
- Rouge1: 0.087
- Rouge2: 0.0117
- Rougel: 0.0565
- Rougelsum: 0.0561
- Gen Len: 191.0

## 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: 1
- eval_batch_size: 1
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.0073        | 1.0   | 1201  | 0.2033          | 0.0963 | 0.0192 | 0.0665 | 0.0663    | 167.0   |
| 0.014         | 2.0   | 2402  | 0.1983          | 0.0642 | 0.0194 | 0.0578 | 0.0578    | 20.0    |
| 0.018         | 3.0   | 3603  | 0.2010          | 0.1027 | 0.0117 | 0.0849 | 0.0855    | 25.0    |
| 0.0119        | 4.0   | 4804  | 0.2012          | 0.0932 | 0.0182 | 0.0649 | 0.0647    | 167.0   |
| 0.0109        | 5.0   | 6005  | 0.2059          | 0.1115 | 0.0203 | 0.0829 | 0.0828    | 52.0    |
| 0.009         | 6.0   | 7206  | 0.2083          | 0.0817 | 0.0132 | 0.0649 | 0.0651    | 29.0    |
| 0.0083        | 7.0   | 8407  | 0.2091          | 0.0785 | 0.0134 | 0.0592 | 0.0592    | 72.0    |
| 0.0081        | 8.0   | 9608  | 0.2113          | 0.095  | 0.0118 | 0.0623 | 0.0622    | 191.0   |
| 0.0072        | 9.0   | 10809 | 0.2142          | 0.0945 | 0.01   | 0.0619 | 0.0617    | 169.0   |
| 0.0072        | 10.0  | 12010 | 0.2163          | 0.0957 | 0.0182 | 0.0844 | 0.0845    | 27.0    |
| 0.0066        | 11.0  | 13211 | 0.2170          | 0.1006 | 0.0166 | 0.0652 | 0.0651    | 97.0    |
| 0.0062        | 12.0  | 14412 | 0.2189          | 0.0852 | 0.0122 | 0.0529 | 0.0526    | 206.0   |
| 0.0062        | 13.0  | 15613 | 0.2208          | 0.0967 | 0.0195 | 0.0855 | 0.086     | 24.0    |
| 0.0059        | 14.0  | 16814 | 0.2218          | 0.0783 | 0.0113 | 0.063  | 0.0629    | 43.0    |
| 0.0057        | 15.0  | 18015 | 0.2212          | 0.0961 | 0.0246 | 0.0786 | 0.0786    | 30.0    |
| 0.0054        | 16.0  | 19216 | 0.2248          | 0.1014 | 0.0211 | 0.0761 | 0.0763    | 79.0    |
| 0.0052        | 17.0  | 20417 | 0.2271          | 0.0874 | 0.0171 | 0.0775 | 0.0774    | 21.0    |
| 0.0051        | 18.0  | 21618 | 0.2268          | 0.0914 | 0.0138 | 0.0595 | 0.0592    | 160.0   |
| 0.0049        | 19.0  | 22819 | 0.2285          | 0.091  | 0.014  | 0.0594 | 0.0591    | 160.0   |
| 0.0048        | 20.0  | 24020 | 0.2283          | 0.087  | 0.0117 | 0.0565 | 0.0561    | 191.0   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
