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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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- summarization |
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- generated_from_trainer |
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datasets: |
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- web_nlg |
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metrics: |
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- rouge |
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model-index: |
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- name: mt5-small-finetuned-amazon-en-es |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: web_nlg |
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type: web_nlg |
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config: en |
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split: validation |
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args: en |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 76.7573 |
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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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# mt5-small-finetuned-amazon-en-es |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the web_nlg dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1274 |
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- Rouge1: 76.7573 |
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- Rouge2: 70.2881 |
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- Rougel: 74.6384 |
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- Rougelsum: 74.6743 |
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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: 5.6e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
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| 1.9276 | 1.0 | 4429 | 0.4272 | 68.6843 | 56.7537 | 65.8818 | 65.9389 | |
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| 0.5548 | 2.0 | 8858 | 0.2903 | 72.0968 | 62.884 | 69.6164 | 69.6271 | |
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| 0.3936 | 3.0 | 13287 | 0.2308 | 73.8306 | 65.8224 | 71.4996 | 71.4971 | |
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| 0.3093 | 4.0 | 17716 | 0.1632 | 75.0861 | 67.7273 | 72.9128 | 72.9615 | |
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| 0.2592 | 5.0 | 22145 | 0.1484 | 75.7699 | 68.7078 | 73.5831 | 73.5905 | |
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| 0.2295 | 6.0 | 26574 | 0.1353 | 76.4394 | 69.689 | 74.3168 | 74.3496 | |
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| 0.2117 | 7.0 | 31003 | 0.1289 | 76.6532 | 69.9438 | 74.5065 | 74.5616 | |
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| 0.2026 | 8.0 | 35432 | 0.1274 | 76.7573 | 70.2881 | 74.6384 | 74.6743 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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