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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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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: mt5-small-task3-dataset3 |
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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-small-task3-dataset3 |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4093 |
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- Accuracy: 0.128 |
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- Mse: 1.5841 |
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- Log-distance: 0.6809 |
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- S Score: 0.4800 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 12 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Mse | Log-distance | S Score | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------------:|:-------:| |
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| 2.1991 | 1.0 | 250 | 1.5275 | 0.106 | 1.7120 | 0.7824 | 0.4048 | |
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| 2.1115 | 2.0 | 500 | 1.5009 | 0.106 | 1.7469 | 0.8062 | 0.3844 | |
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| 1.8295 | 3.0 | 750 | 1.4483 | 0.108 | 1.7239 | 0.7902 | 0.3972 | |
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| 1.7033 | 4.0 | 1000 | 1.4335 | 0.112 | 1.7052 | 0.7759 | 0.4088 | |
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| 1.6426 | 5.0 | 1250 | 1.4224 | 0.12 | 1.5337 | 0.6427 | 0.5112 | |
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| 1.5923 | 6.0 | 1500 | 1.4236 | 0.126 | 1.6061 | 0.7015 | 0.4628 | |
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| 1.5529 | 7.0 | 1750 | 1.4284 | 0.122 | 1.5984 | 0.6967 | 0.4676 | |
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| 1.546 | 8.0 | 2000 | 1.4132 | 0.124 | 1.6032 | 0.6948 | 0.4704 | |
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| 1.5364 | 9.0 | 2250 | 1.4306 | 0.116 | 1.6403 | 0.7282 | 0.4460 | |
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| 1.5365 | 10.0 | 2500 | 1.4107 | 0.118 | 1.5702 | 0.6681 | 0.4948 | |
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| 1.5145 | 11.0 | 2750 | 1.4182 | 0.118 | 1.6041 | 0.7063 | 0.4596 | |
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| 1.5103 | 12.0 | 3000 | 1.4093 | 0.128 | 1.5841 | 0.6809 | 0.4800 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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