---
license: mit
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mbart-large-50-finetuned-stocks-event-1
  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. -->

# mbart-large-50-finetuned-stocks-event-1

This model is a fine-tuned version of [jiaoqsh/mbart-large-50-finetuned-stock-dividend](https://huggingface.co/jiaoqsh/mbart-large-50-finetuned-stock-dividend) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1419
- Rouge1: 0.9120
- Rouge2: 0.8056
- Rougel: 0.9120
- Rougelsum: 0.9120

## 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: 5.6e-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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 0.3179        | 1.0   | 20   | 0.1784          | 0.8727 | 0.7639 | 0.8704 | 0.8727    |
| 0.0569        | 2.0   | 40   | 0.0822          | 0.9167 | 0.8333 | 0.9167 | 0.9144    |
| 0.0284        | 3.0   | 60   | 0.1842          | 0.9120 | 0.8194 | 0.9144 | 0.9120    |
| 0.0153        | 4.0   | 80   | 0.1448          | 0.9236 | 0.8472 | 0.9213 | 0.9236    |
| 0.0066        | 5.0   | 100  | 0.1271          | 0.9444 | 0.875  | 0.9421 | 0.9444    |
| 0.0013        | 6.0   | 120  | 0.1381          | 0.9190 | 0.8194 | 0.9213 | 0.9213    |
| 0.0083        | 7.0   | 140  | 0.1414          | 0.9190 | 0.8194 | 0.9213 | 0.9213    |
| 0.0002        | 8.0   | 160  | 0.1419          | 0.9120 | 0.8056 | 0.9120 | 0.9120    |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2