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--- |
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license: mit |
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base_model: cointegrated/rut5-base-multitask |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: finetune_t5_base_only_hack |
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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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# finetune_t5_base_only_hack |
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This model is a fine-tuned version of [cointegrated/rut5-base-multitask](https://huggingface.co/cointegrated/rut5-base-multitask) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4584 |
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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: 0.0004 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 32 |
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- total_train_batch_size: 256 |
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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: 100 |
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- num_epochs: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.8215 | 3.86 | 150 | 1.5392 | |
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| 1.579 | 7.72 | 300 | 1.4584 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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