---
license: mit
base_model: VietAI/vit5-base
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: mrc-vit5-dsc
  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. -->

# mrc-vit5-dsc

This model is a fine-tuned version of [VietAI/vit5-base](https://huggingface.co/VietAI/vit5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6093
- Exact Match: 0.7382
- F1: 0.8663

## 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: 6
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Exact Match | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:-----------:|:------:|
| 0.7044        | 1.0   | 4240  | 0.6239          | 0.6669      | 0.8277 |
| 0.5249        | 2.0   | 8480  | 0.5740          | 0.7000      | 0.8584 |
| 0.3262        | 3.0   | 12720 | 0.7052          | 0.7215      | 0.8609 |
| 0.2361        | 4.0   | 16960 | 1.1596          | 0.7305      | 0.8601 |
| 0.1454        | 5.0   | 21200 | 1.6093          | 0.7382      | 0.8663 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.2.1
- Datasets 2.19.1
- Tokenizers 0.19.1