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-320-output
  results: []
---

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# fine-tuned-BioBARTv2-20-epochs-1024-input-320-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: 0.7867
- Rouge1: 0.1624
- Rouge2: 0.0352
- Rougel: 0.1185
- Rougelsum: 0.1188
- Gen Len: 37.64

## 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  | 6.3285          | 0.0632 | 0.0007 | 0.0552 | 0.0555    | 37.84   |
| No log        | 2.0   | 302  | 0.9332          | 0.1075 | 0.0282 | 0.0825 | 0.0825    | 62.51   |
| No log        | 3.0   | 453  | 0.8092          | 0.0826 | 0.0196 | 0.0629 | 0.0622    | 28.26   |
| 4.0641        | 4.0   | 604  | 0.7617          | 0.1106 | 0.0346 | 0.0814 | 0.0814    | 32.19   |
| 4.0641        | 5.0   | 755  | 0.7385          | 0.1359 | 0.0266 | 0.1043 | 0.1048    | 35.85   |
| 4.0641        | 6.0   | 906  | 0.7296          | 0.1507 | 0.0296 | 0.1099 | 0.1112    | 45.66   |
| 0.6482        | 7.0   | 1057 | 0.7225          | 0.1315 | 0.026  | 0.0978 | 0.0992    | 36.35   |
| 0.6482        | 8.0   | 1208 | 0.7165          | 0.1573 | 0.0302 | 0.1218 | 0.1222    | 42.68   |
| 0.6482        | 9.0   | 1359 | 0.7191          | 0.1445 | 0.0307 | 0.1155 | 0.1156    | 30.12   |
| 0.4567        | 10.0  | 1510 | 0.7281          | 0.1827 | 0.0423 | 0.1403 | 0.1408    | 47.87   |
| 0.4567        | 11.0  | 1661 | 0.7320          | 0.1603 | 0.0311 | 0.1193 | 0.1193    | 33.69   |
| 0.4567        | 12.0  | 1812 | 0.7395          | 0.1697 | 0.0357 | 0.1267 | 0.1267    | 46.9    |
| 0.4567        | 13.0  | 1963 | 0.7515          | 0.1442 | 0.0297 | 0.1064 | 0.1065    | 31.28   |
| 0.3275        | 14.0  | 2114 | 0.7549          | 0.1767 | 0.0306 | 0.1255 | 0.1259    | 49.23   |
| 0.3275        | 15.0  | 2265 | 0.7680          | 0.1475 | 0.0327 | 0.1054 | 0.1057    | 37.28   |
| 0.3275        | 16.0  | 2416 | 0.7760          | 0.1525 | 0.0337 | 0.1065 | 0.1072    | 38.87   |
| 0.2407        | 17.0  | 2567 | 0.7797          | 0.1543 | 0.039  | 0.1163 | 0.1168    | 38.67   |
| 0.2407        | 18.0  | 2718 | 0.7845          | 0.1794 | 0.0382 | 0.13   | 0.1305    | 38.47   |
| 0.2407        | 19.0  | 2869 | 0.7860          | 0.1645 | 0.0372 | 0.1218 | 0.1219    | 36.26   |
| 0.1982        | 20.0  | 3020 | 0.7867          | 0.1624 | 0.0352 | 0.1185 | 0.1188    | 37.64   |


### Framework versions

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