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--- |
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license: apache-2.0 |
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base_model: google/mt5-small |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: reviews_sum |
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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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# reviews_sum |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.8535 |
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- Rouge1: 0.0273 |
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- Rouge2: 0.0 |
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- Rougel: 0.0277 |
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- Rougelsum: 0.0274 |
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- Gen Len: 19.0 |
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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: 0.001 |
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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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- 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: 10 |
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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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| No log | 1.0 | 395 | 3.4194 | 0.0339 | 0.0 | 0.0338 | 0.0338 | 19.0 | |
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| 4.9137 | 2.0 | 790 | 3.0496 | 0.0339 | 0.0 | 0.0338 | 0.0338 | 19.0 | |
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| 3.1919 | 3.0 | 1185 | 2.9381 | 0.0339 | 0.0 | 0.0338 | 0.0338 | 19.0 | |
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| 2.8961 | 4.0 | 1580 | 2.8875 | 0.0339 | 0.0 | 0.0338 | 0.0338 | 19.0 | |
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| 2.8961 | 5.0 | 1975 | 2.8487 | 0.0 | 0.0 | 0.0 | 0.0 | 19.0 | |
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| 2.72 | 6.0 | 2370 | 2.8328 | 0.0339 | 0.0 | 0.0338 | 0.0338 | 19.0 | |
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| 2.5695 | 7.0 | 2765 | 2.8332 | 0.0273 | 0.0 | 0.0277 | 0.0274 | 19.0 | |
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| 2.4644 | 8.0 | 3160 | 2.8412 | 0.0 | 0.0 | 0.0 | 0.0 | 19.0 | |
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| 2.3847 | 9.0 | 3555 | 2.8358 | 0.0339 | 0.0 | 0.0338 | 0.0338 | 19.0 | |
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| 2.3847 | 10.0 | 3950 | 2.8535 | 0.0273 | 0.0 | 0.0277 | 0.0274 | 19.0 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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