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End of training
Browse files- README.md +13 -15
- logs/events.out.tfevents.1711099495.5da5938990cd.1513.0 +3 -0
- logs/events.out.tfevents.1711099590.5da5938990cd.4571.0 +3 -0
- logs/events.out.tfevents.1711099755.5da5938990cd.5456.0 +3 -0
- logs/events.out.tfevents.1711105019.5da5938990cd.5456.1 +3 -0
- model.safetensors +1 -1
- tokenizer.json +1 -6
- training_args.bin +1 -1
README.md
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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:
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- Rouge1:
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- Rouge2:
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- Rougel:
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- Rougelsum:
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- Gen Len: 16.
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size:
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- eval_batch_size:
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- seed: 42
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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:
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### Training results
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| Training Loss | Epoch | Step
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| 1.496 | 2.0 | 7366 | 1.6228 | 52.8317 | 29.8327 | 41.7287 | 46.3648 | 16.8071 |
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| 1.1959 | 3.0 | 11049 | 1.6419 | 53.6738 | 30.2857 | 42.5458 | 47.2315 | 16.906 |
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### Framework versions
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- Transformers 4.38.2
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- Pytorch 2.1
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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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: 0.6377
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- Rouge1: 51.4583
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- Rouge2: 28.5387
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- Rougel: 40.9957
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- Rougelsum: 45.4297
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- Gen Len: 16.1661
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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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: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
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| 0.5898 | 1.0 | 7366 | 0.6377 | 51.4583 | 28.5387 | 40.9957 | 45.4297 | 16.1661 |
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### Framework versions
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- Transformers 4.38.2
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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tokenizer.json
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