---
base_model: checkpoint_global_step_200000
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: NoteChat-BioBART
  results: []
---

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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/fine-tuning-large-language-model/huggingface/runs/avtpaj92)
# NoteChat-BioBART

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: 2.0020
- Rouge1: 0.0816
- Rouge2: 0.0373
- Rougel: 0.0711
- Rougelsum: 0.074
- Gen Len: 20.0

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 3.6113        | 1.0   | 3726  | 3.5345          | 0.0729 | 0.0245 | 0.0639 | 0.0667    | 20.0    |
| 3.2014        | 2.0   | 7452  | 3.1318          | 0.0701 | 0.0228 | 0.0619 | 0.0643    | 20.0    |
| 2.9394        | 3.0   | 11178 | 2.8865          | 0.0733 | 0.0255 | 0.0653 | 0.0678    | 20.0    |
| 2.7238        | 4.0   | 14904 | 2.6827          | 0.0759 | 0.0291 | 0.0673 | 0.0695    | 20.0    |
| 2.5805        | 5.0   | 18630 | 2.5151          | 0.0774 | 0.0311 | 0.0673 | 0.07      | 20.0    |
| 2.4169        | 6.0   | 22356 | 2.3876          | 0.0799 | 0.0329 | 0.0686 | 0.0717    | 20.0    |
| 2.2721        | 7.0   | 26082 | 2.2933          | 0.081  | 0.0345 | 0.0706 | 0.0734    | 20.0    |
| 2.207         | 8.0   | 29808 | 2.2572          | 0.0812 | 0.035  | 0.071  | 0.0737    | 20.0    |
| 2.1144        | 9.0   | 33534 | 2.1707          | 0.081  | 0.0352 | 0.0706 | 0.0735    | 20.0    |
| 2.0559        | 10.0  | 37260 | 2.1287          | 0.0814 | 0.0351 | 0.0694 | 0.0728    | 20.0    |
| 1.9991        | 11.0  | 40986 | 2.0978          | 0.081  | 0.0356 | 0.0705 | 0.0734    | 20.0    |
| 1.9552        | 12.0  | 44712 | 2.0716          | 0.0812 | 0.0362 | 0.0709 | 0.0737    | 20.0    |
| 1.9006        | 13.0  | 48438 | 2.0657          | 0.081  | 0.0364 | 0.0711 | 0.0739    | 20.0    |
| 1.8592        | 14.0  | 52164 | 2.0483          | 0.0812 | 0.0362 | 0.0704 | 0.0734    | 20.0    |
| 1.8453        | 15.0  | 55890 | 2.0314          | 0.0815 | 0.0375 | 0.0716 | 0.0744    | 20.0    |
| 1.8113        | 16.0  | 59616 | 2.0129          | 0.081  | 0.0367 | 0.0708 | 0.0735    | 20.0    |
| 1.7864        | 17.0  | 63342 | 2.0055          | 0.0815 | 0.0371 | 0.0711 | 0.074     | 20.0    |
| 1.781         | 18.0  | 67068 | 2.0136          | 0.0809 | 0.0368 | 0.0708 | 0.0737    | 20.0    |
| 1.7774        | 19.0  | 70794 | 2.0024          | 0.0815 | 0.0372 | 0.071  | 0.0739    | 20.0    |
| 1.7345        | 20.0  | 74520 | 2.0020          | 0.0816 | 0.0373 | 0.0711 | 0.074     | 20.0    |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1