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--- |
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license: apache-2.0 |
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base_model: google/mt5-base |
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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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- bleu |
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model-index: |
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- name: skilltext |
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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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# skilltext |
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This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: nan |
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- Rouge1: 0.431 |
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- Rouge2: 0.0 |
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- Rougel: 0.431 |
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- Rougelsum: 0.431 |
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- Bleu: 0.0322 |
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- Gen Len: 11.75 |
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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: 2e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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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: 30 |
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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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu | Gen Len | |
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|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:------:|:-------:| |
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| No log | 0.8065 | 50 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| No log | 1.6129 | 100 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| No log | 2.4194 | 150 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| No log | 3.2258 | 200 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| No log | 4.0323 | 250 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| No log | 4.8387 | 300 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| No log | 5.6452 | 350 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| No log | 6.4516 | 400 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| No log | 7.2581 | 450 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 8.0645 | 500 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 8.8710 | 550 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 9.6774 | 600 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 10.4839 | 650 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 11.2903 | 700 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 12.0968 | 750 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 12.9032 | 800 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 13.7097 | 850 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 14.5161 | 900 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 15.3226 | 950 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 16.1290 | 1000 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 16.9355 | 1050 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 17.7419 | 1100 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 18.5484 | 1150 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 19.3548 | 1200 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 20.1613 | 1250 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 20.9677 | 1300 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 21.7742 | 1350 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 22.5806 | 1400 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 23.3871 | 1450 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 24.1935 | 1500 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 25.0 | 1550 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 25.8065 | 1600 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 26.6129 | 1650 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 27.4194 | 1700 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 28.2258 | 1750 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 29.0323 | 1800 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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| 0.0 | 29.8387 | 1850 | nan | 0.431 | 0.0 | 0.431 | 0.431 | 0.0322 | 11.75 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.2.2 |
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- Datasets 2.12.0 |
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- Tokenizers 0.19.1 |
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