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--- |
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license: apache-2.0 |
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base_model: t5-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- bleu |
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- wer |
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model-index: |
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- name: randomization_model |
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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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# randomization_model |
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This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.6576 |
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- Bleu: 0.0001 |
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- Wer: 0.9576 |
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- Gen Len: 18.9986 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 2 |
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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 | Bleu | Wer | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:-------:| |
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| 2.5767 | 0.16 | 1000 | 1.6626 | 0.0001 | 0.954 | 18.9985 | |
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| 1.9533 | 0.32 | 2000 | 1.5147 | 0.0001 | 0.9524 | 18.9986 | |
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| 1.8318 | 0.48 | 3000 | 1.4392 | 0.0001 | 0.9518 | 18.9986 | |
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| 1.7626 | 0.64 | 4000 | 1.3857 | 0.0001 | 0.9514 | 18.9986 | |
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| 1.7199 | 0.8 | 5000 | 1.3553 | 0.0001 | 0.951 | 18.9988 | |
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| 1.6727 | 0.96 | 6000 | 1.3325 | 0.0001 | 0.9507 | 18.9986 | |
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| 1.9628 | 1.12 | 7000 | 1.8528 | 0.0001 | 0.9524 | 18.9988 | |
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| 2.9138 | 1.28 | 8000 | 2.6299 | 0.0001 | 0.9568 | 18.9986 | |
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| 3.5506 | 1.44 | 9000 | 2.7483 | 0.0001 | 0.958 | 18.9987 | |
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| 3.5214 | 1.6 | 10000 | 2.7007 | 0.0001 | 0.9578 | 18.9986 | |
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| 3.4669 | 1.76 | 11000 | 2.6699 | 0.0001 | 0.9576 | 18.9986 | |
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| 3.4448 | 1.92 | 12000 | 2.6576 | 0.0001 | 0.9576 | 18.9986 | |
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### Framework versions |
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- Transformers 4.37.1 |
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- Pytorch 2.3.0.dev20240122+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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