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---
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
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