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--- |
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language: |
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- en |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- cstop_artificial |
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model-index: |
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- name: byt5-base-cstop_artificial |
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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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# byt5-base-cstop_artificial |
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This model is a fine-tuned version of [google/byt5-base](https://huggingface.co/google/byt5-base) on the cstop_artificial dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0461 |
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- Exact Match: 0.7996 |
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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: 0.001 |
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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: 64 |
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- total_train_batch_size: 512 |
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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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- training_steps: 3000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Exact Match | |
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|:-------------:|:------:|:----:|:---------------:|:-----------:| |
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| 0.2563 | 28.5 | 200 | 0.0461 | 0.0376 | |
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| 0.0065 | 57.13 | 400 | 0.0563 | 0.0376 | |
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| 0.0021 | 85.63 | 600 | 0.0592 | 0.0358 | |
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| 0.0013 | 114.25 | 800 | 0.0569 | 0.0376 | |
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| 0.0008 | 142.75 | 1000 | 0.0675 | 0.0358 | |
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| 0.0007 | 171.38 | 1200 | 0.0627 | 0.0394 | |
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| 0.0004 | 199.88 | 1400 | 0.0677 | 0.0358 | |
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| 0.0003 | 228.5 | 1600 | 0.0650 | 0.0376 | |
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| 0.0002 | 257.13 | 1800 | 0.0693 | 0.0394 | |
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| 0.0002 | 285.63 | 2000 | 0.0721 | 0.0394 | |
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| 0.0002 | 314.25 | 2200 | 0.0714 | 0.0376 | |
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| 0.0002 | 342.75 | 2400 | 0.0701 | 0.0394 | |
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| 0.0002 | 371.38 | 2600 | 0.0750 | 0.0394 | |
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| 0.0001 | 399.88 | 2800 | 0.0739 | 0.0394 | |
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| 0.0001 | 428.5 | 3000 | 0.0745 | 0.0394 | |
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### Framework versions |
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- Transformers 4.24.0 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.0 |
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- Tokenizers 0.13.2 |
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