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--- |
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license: apache-2.0 |
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base_model: google/mt5-large |
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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: MT5-large_NO-idun-20epoch-earlystopping |
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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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# MT5-large_NO-idun-20epoch-earlystopping |
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This model is a fine-tuned version of [google/mt5-large](https://huggingface.co/google/mt5-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6061 |
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- Rouge1: 41.2146 |
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- Rouge2: 18.153 |
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- Rougel: 28.4036 |
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- Rougelsum: 36.8514 |
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- Gen Len: 111.1064 |
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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: 2 |
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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: 8 |
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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: 20 |
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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 | 0.98 | 46 | 13.1717 | 15.636 | 4.987 | 10.443 | 14.3841 | 119.9149 | |
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| No log | 1.99 | 93 | 7.7651 | 10.907 | 1.4566 | 6.9291 | 10.152 | 127.0 | |
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| No log | 2.99 | 140 | 6.4230 | 18.8954 | 0.4957 | 13.2179 | 17.1171 | 127.0 | |
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| No log | 4.0 | 187 | 2.1315 | 37.1306 | 13.4104 | 21.2261 | 33.0925 | 127.0 | |
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| No log | 4.98 | 233 | 1.7761 | 37.6703 | 14.7962 | 22.835 | 34.0213 | 113.5638 | |
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| No log | 5.99 | 280 | 1.6807 | 38.6245 | 15.7401 | 24.5743 | 34.5933 | 113.2340 | |
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| No log | 6.99 | 327 | 1.6484 | 38.7899 | 15.737 | 24.9265 | 34.6166 | 114.3404 | |
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| No log | 8.0 | 374 | 1.6156 | 39.3812 | 15.7133 | 24.979 | 35.2788 | 120.0319 | |
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| No log | 8.98 | 420 | 1.6138 | 40.0966 | 17.4991 | 26.5925 | 36.5511 | 117.2234 | |
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| No log | 9.99 | 467 | 1.6152 | 40.3623 | 17.7244 | 27.0847 | 36.2108 | 113.2128 | |
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| 6.3618 | 10.99 | 514 | 1.6102 | 41.2763 | 18.0108 | 27.6185 | 37.1836 | 113.1064 | |
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| 6.3618 | 12.0 | 561 | 1.6070 | 41.2369 | 17.8711 | 27.3781 | 36.9853 | 115.7766 | |
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| 6.3618 | 12.98 | 607 | 1.6087 | 42.0737 | 18.414 | 27.8849 | 38.1238 | 113.3404 | |
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| 6.3618 | 13.99 | 654 | 1.6038 | 41.4279 | 17.8899 | 27.79 | 36.929 | 115.1383 | |
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| 6.3618 | 14.99 | 701 | 1.6061 | 40.8051 | 17.4437 | 27.1414 | 36.494 | 113.8936 | |
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| 6.3618 | 16.0 | 748 | 1.6074 | 41.8104 | 18.0504 | 27.934 | 37.3843 | 114.8511 | |
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| 6.3618 | 16.98 | 794 | 1.6053 | 41.4314 | 17.955 | 27.7884 | 36.9083 | 114.3830 | |
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| 6.3618 | 17.99 | 841 | 1.6057 | 41.8533 | 18.0219 | 27.7616 | 37.4008 | 113.2128 | |
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| 6.3618 | 18.99 | 888 | 1.6060 | 41.5846 | 18.3563 | 28.4177 | 37.1366 | 112.1915 | |
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| 6.3618 | 19.68 | 920 | 1.6061 | 41.2146 | 18.153 | 28.4036 | 36.8514 | 111.1064 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.2 |
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