transformers tensorboard safetensors bart text2text-generation generated_from_trainer base_model:bart-base autotrain_compatible endpoints_compatible region:us
---
base_model: bart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: fine-tuned-bart-10-epochs-1500-input-512-output
  results: []
---

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# fine-tuned-bart-10-epochs-1500-input-512-output

This model is a fine-tuned version of [bart-base](https://huggingface.co/bart-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8625
- Rouge1: 0.165
- Rouge2: 0.0393
- Rougel: 0.1287
- Rougelsum: 0.1279
- Gen Len: 33.11

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 151  | 2.4626          | 0.0074 | 0.0    | 0.0072 | 0.0071    | 4.31    |
| No log        | 2.0   | 302  | 1.0378          | 0.0601 | 0.0109 | 0.0554 | 0.0557    | 7.64    |
| No log        | 3.0   | 453  | 0.9493          | 0.0832 | 0.0204 | 0.0639 | 0.0638    | 21.16   |
| 3.1513        | 4.0   | 604  | 0.9068          | 0.1305 | 0.0335 | 0.1007 | 0.1004    | 29.73   |
| 3.1513        | 5.0   | 755  | 0.8867          | 0.1605 | 0.0399 | 0.1177 | 0.1176    | 61.33   |
| 3.1513        | 6.0   | 906  | 0.8760          | 0.1603 | 0.0306 | 0.1332 | 0.133     | 31.76   |
| 0.7578        | 7.0   | 1057 | 0.8677          | 0.1549 | 0.0431 | 0.1168 | 0.1168    | 34.18   |
| 0.7578        | 8.0   | 1208 | 0.8624          | 0.161  | 0.0403 | 0.1172 | 0.1168    | 37.92   |
| 0.7578        | 9.0   | 1359 | 0.8639          | 0.1542 | 0.0374 | 0.1219 | 0.1213    | 31.73   |
| 0.5902        | 10.0  | 1510 | 0.8625          | 0.165  | 0.0393 | 0.1287 | 0.1279    | 33.11   |


### Framework versions

- Transformers 4.36.2
- Pytorch 1.12.1+cu113
- Datasets 2.16.1
- Tokenizers 0.15.0
