End of training
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README.md
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---
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license: mit
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base_model: VietAI/vit5-base
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tags:
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- generated_from_trainer
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metrics:
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- f1
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- accuracy
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model-index:
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- name: vit5-base_sentiment
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# vit5-base_sentiment
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This model is a fine-tuned version of [VietAI/vit5-base](https://huggingface.co/VietAI/vit5-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8273
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- F1: 0.6438
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- Accuracy: 0.6875
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 32
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy |
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|:-------------:|:------:|:----:|:---------------:|:------:|:--------:|
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| 0.8932 | 0.9984 | 312 | 0.7780 | 0.6134 | 0.669 |
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| 0.7353 | 2.0 | 625 | 0.7549 | 0.6252 | 0.6745 |
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| 0.6538 | 2.9984 | 937 | 0.7768 | 0.6320 | 0.6805 |
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| 0.5827 | 4.0 | 1250 | 0.7904 | 0.6379 | 0.6865 |
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| 0.5204 | 4.992 | 1560 | 0.8273 | 0.6438 | 0.6875 |
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### Framework versions
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- Transformers 4.44.0
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- Pytorch 2.4.0
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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runs/Aug20_14-30-52_speech.local/events.out.tfevents.1724139054.speech.local
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runs/Aug20_14-30-52_speech.local/events.out.tfevents.1724142356.speech.local
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