---
license: mit
base_model: october-sd/mbart-large-50-finetuned-latest3
tags:
- summarization
- generated_from_trainer
model-index:
- name: mbart-large-50-finetuned-8
  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-8

This model is a fine-tuned version of [october-sd/mbart-large-50-finetuned-latest3](https://huggingface.co./october-sd/mbart-large-50-finetuned-latest3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4685

## 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 183  | 2.4781          |
| No log        | 2.0   | 367  | 2.4710          |
| No log        | 3.0   | 550  | 2.4703          |
| No log        | 3.99  | 732  | 2.4685          |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.15.0
- Tokenizers 0.15.2