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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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- wer |
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base_model: google/mt5-small |
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model-index: |
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- name: nep-spell-mt5-small-0 |
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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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# nep-spell-mt5-small-0 |
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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: 1.6065 |
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- Accuracy: 0.0 |
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- Precision: 0.0 |
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- Recall: 0.0 |
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- F1: 0.0 |
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- Wer: 7.0137 |
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- Cer: 13.4164 |
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- Chrf: 1.5380 |
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- Exact Match: 0.0 |
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- Bertscore:precision: 0.4936 |
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- Bertscore:recall: 0.5422 |
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- Bertscore:f1: 0.5139 |
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- Ter: 701.3722 |
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- Blerurt: -0.5287 |
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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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Wer | Cer | Chrf | Exact Match | Bertscore:precision | Bertscore:recall | Bertscore:f1 | Ter | Blerurt | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:---:|:-------:|:-------:|:------:|:-----------:|:-------------------:|:----------------:|:------------:|:---------:|:-------:| |
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| 39.0737 | 0.39 | 500 | 14.0796 | 0.0 | 0.0 | 0.0 | 0.0 | 28.9335 | 58.5317 | 0.3292 | 0.0 | 0.3772 | 0.5413 | 0.4436 | 2893.3486 | -0.9012 | |
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| 4.5775 | 0.79 | 1000 | 1.6065 | 0.0 | 0.0 | 0.0 | 0.0 | 7.0137 | 13.4164 | 1.5380 | 0.0 | 0.4936 | 0.5422 | 0.5139 | 701.3722 | -0.5287 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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