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--- |
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license: bigscience-bloom-rail-1.0 |
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langs: |
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- es |
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tags: |
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- generated_from_trainer |
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- summarization |
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- Spanish summarizing |
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model-index: |
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- name: bloom-560m-finetuned-wikilingua-spanish-summarization |
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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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# bloom-560m-finetuned-wikilingua-spanish-summarization |
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This model is a fine-tuned version of [bigscience/bloom-560m](https://huggingface.co/bigscience/bloom-560m) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.1223 |
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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: 5e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 4 |
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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: 2 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 2.4768 | 0.07 | 500 | 2.4828 | |
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| 2.428 | 0.14 | 1000 | 2.4125 | |
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| 2.4 | 0.2 | 1500 | 2.3927 | |
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| 2.3685 | 0.27 | 2000 | 2.3506 | |
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| 2.3287 | 0.34 | 2500 | 2.3340 | |
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| 2.3196 | 0.41 | 3000 | 2.3284 | |
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| 2.2885 | 0.48 | 3500 | 2.3005 | |
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| 2.2646 | 0.55 | 4000 | 2.2944 | |
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| 2.2676 | 0.68 | 5000 | 2.2575 | |
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| 2.2267 | 0.82 | 6000 | 2.2281 | |
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| 2.1971 | 0.95 | 7000 | 2.2018 | |
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| 2.009 | 1.09 | 8000 | 2.1925 | |
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| 1.9989 | 1.23 | 9000 | 2.1765 | |
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| 2.0131 | 1.36 | 10000 | 2.1666 | |
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| 1.9765 | 1.5 | 11000 | 2.1514 | |
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| 1.9449 | 1.64 | 12000 | 2.1404 | |
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| 1.9399 | 1.77 | 13000 | 2.1297 | |
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| 1.957 | 1.91 | 14000 | 2.1223 | |
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### Framework versions |
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- Transformers 4.23.0.dev0 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.5.1 |
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- Tokenizers 0.13.0 |
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