transformers tensorboard safetensors bart text2text-generation generated_from_trainer base_model:GanjinZero/biobart-v2-base license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: GanjinZero/biobart-v2-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: fine-tuned-BART-2048-inputs-20-epochs
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# fine-tuned-BART-2048-inputs-20-epochs

This model is a fine-tuned version of [GanjinZero/biobart-v2-base](https://huggingface.co/GanjinZero/biobart-v2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7640
- Rouge1: 0.318
- Rouge2: 0.1243
- Rougel: 0.2884
- Rougelsum: 0.2894
- Gen Len: 15.42

## 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: 8
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 151  | 0.7532          | 0.2007 | 0.0751 | 0.1827 | 0.1821    | 13.29   |
| No log        | 2.0   | 302  | 0.7148          | 0.261  | 0.0836 | 0.2299 | 0.2312    | 13.92   |
| No log        | 3.0   | 453  | 0.6995          | 0.248  | 0.0862 | 0.2195 | 0.2201    | 14.49   |
| 0.724         | 4.0   | 604  | 0.6956          | 0.2944 | 0.1061 | 0.2658 | 0.2665    | 14.31   |
| 0.724         | 5.0   | 755  | 0.7029          | 0.3061 | 0.1203 | 0.2808 | 0.283     | 14.81   |
| 0.724         | 6.0   | 906  | 0.6965          | 0.2848 | 0.1118 | 0.2596 | 0.2584    | 15.0    |
| 0.5016        | 7.0   | 1057 | 0.7097          | 0.2874 | 0.1207 | 0.2558 | 0.2562    | 15.0    |
| 0.5016        | 8.0   | 1208 | 0.7140          | 0.293  | 0.1143 | 0.2617 | 0.2641    | 14.3    |
| 0.5016        | 9.0   | 1359 | 0.7191          | 0.3198 | 0.1222 | 0.2877 | 0.2903    | 14.75   |
| 0.3838        | 10.0  | 1510 | 0.7274          | 0.3127 | 0.1265 | 0.2863 | 0.2874    | 14.82   |
| 0.3838        | 11.0  | 1661 | 0.7312          | 0.3129 | 0.1282 | 0.2821 | 0.2819    | 14.97   |
| 0.3838        | 12.0  | 1812 | 0.7419          | 0.2974 | 0.1123 | 0.2726 | 0.2725    | 14.98   |
| 0.3838        | 13.0  | 1963 | 0.7441          | 0.2945 | 0.1139 | 0.2682 | 0.2681    | 15.1    |
| 0.3153        | 14.0  | 2114 | 0.7490          | 0.2969 | 0.1207 | 0.2743 | 0.2753    | 15.29   |
| 0.3153        | 15.0  | 2265 | 0.7536          | 0.2971 | 0.1116 | 0.2674 | 0.2689    | 14.83   |
| 0.3153        | 16.0  | 2416 | 0.7564          | 0.301  | 0.1078 | 0.271  | 0.2726    | 15.3    |
| 0.2646        | 17.0  | 2567 | 0.7585          | 0.2989 | 0.1117 | 0.2737 | 0.2744    | 15.21   |
| 0.2646        | 18.0  | 2718 | 0.7630          | 0.2944 | 0.1078 | 0.2641 | 0.265     | 15.12   |
| 0.2646        | 19.0  | 2869 | 0.7632          | 0.2986 | 0.1089 | 0.2669 | 0.2683    | 15.25   |
| 0.2428        | 20.0  | 3020 | 0.7640          | 0.318  | 0.1243 | 0.2884 | 0.2894    | 15.42   |


### Framework versions

- Transformers 4.36.2
- Pytorch 1.12.1+cu113
- Datasets 2.15.0
- Tokenizers 0.15.0
