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---
license: mit
base_model: VietAI/vit5-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: vit5-base_sentiment
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. -->
# vit5-base_sentiment
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: 0.8273
- F1: 0.6438
- Accuracy: 0.6875
## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- 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 | F1 | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:------:|:--------:|
| 0.8932 | 0.9984 | 312 | 0.7780 | 0.6134 | 0.669 |
| 0.7353 | 2.0 | 625 | 0.7549 | 0.6252 | 0.6745 |
| 0.6538 | 2.9984 | 937 | 0.7768 | 0.6320 | 0.6805 |
| 0.5827 | 4.0 | 1250 | 0.7904 | 0.6379 | 0.6865 |
| 0.5204 | 4.992 | 1560 | 0.8273 | 0.6438 | 0.6875 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.20.0
- Tokenizers 0.19.1
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