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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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model-index: |
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- name: t5-small-vanilla-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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# t5-small-vanilla-cstop_artificial |
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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: 0.1506 |
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- Exact Match: 0.5725 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 32 |
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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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| 1.4041 | 28.5 | 200 | 0.1008 | 0.4758 | |
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| 0.047 | 57.13 | 400 | 0.1029 | 0.5367 | |
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| 0.021 | 85.63 | 600 | 0.1077 | 0.5617 | |
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| 0.012 | 114.25 | 800 | 0.1214 | 0.5689 | |
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| 0.0079 | 142.75 | 1000 | 0.1273 | 0.5671 | |
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| 0.0809 | 171.38 | 1200 | 0.1192 | 0.5653 | |
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| 0.0063 | 199.88 | 1400 | 0.1329 | 0.5653 | |
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| 0.0042 | 228.5 | 1600 | 0.1402 | 0.5707 | |
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| 0.0036 | 257.13 | 1800 | 0.1335 | 0.5617 | |
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| 0.0029 | 285.63 | 2000 | 0.1423 | 0.5689 | |
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| 0.0023 | 314.25 | 2200 | 0.1515 | 0.5671 | |
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| 0.0019 | 342.75 | 2400 | 0.1569 | 0.5689 | |
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| 0.0018 | 371.38 | 2600 | 0.1517 | 0.5689 | |
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| 0.0016 | 399.88 | 2800 | 0.1527 | 0.5725 | |
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| 0.0016 | 428.5 | 3000 | 0.1506 | 0.5725 | |
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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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