---
base_model: facebook/mbart-large-50-many-to-many-mmt
tags:
- generated_from_trainer
model-index:
- name: mbart-large-50-many-to-many-mmt-finetuned-human-to-assistant
  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. -->

[<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/peterparkercar321-amrita-vishwa-vidyapeetham/huggingface/runs/97jf138x)
# mbart-large-50-many-to-many-mmt-finetuned-human-to-assistant

This model is a fine-tuned version of [facebook/mbart-large-50-many-to-many-mmt](https://huggingface.co/facebook/mbart-large-50-many-to-many-mmt) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5397

## 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: 3e-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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 9    | 1.3946          |
| No log        | 2.0   | 18   | 1.3488          |
| No log        | 3.0   | 27   | 1.3852          |
| No log        | 4.0   | 36   | 1.4675          |
| No log        | 5.0   | 45   | 1.5198          |
| No log        | 6.0   | 54   | 1.5201          |
| No log        | 7.0   | 63   | 1.5057          |
| No log        | 8.0   | 72   | 1.4997          |
| No log        | 9.0   | 81   | 1.5251          |
| No log        | 10.0  | 90   | 1.5397          |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1