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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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- top_v2 |
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model-index: |
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- name: t5-base-pointer-top_v2 |
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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-base-pointer-top_v2 |
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This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the top_v2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0256 |
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- Exact Match: 0.8517 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 128 |
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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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| 1.4545 | 0.82 | 200 | 0.2542 | 0.1294 | |
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| 0.1878 | 1.65 | 400 | 0.0668 | 0.2128 | |
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| 0.0796 | 2.47 | 600 | 0.0466 | 0.2276 | |
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| 0.0536 | 3.29 | 800 | 0.0356 | 0.2309 | |
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| 0.0424 | 4.12 | 1000 | 0.0317 | 0.2328 | |
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| 0.0356 | 4.94 | 1200 | 0.0295 | 0.2340 | |
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| 0.0306 | 5.76 | 1400 | 0.0288 | 0.2357 | |
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| 0.0277 | 6.58 | 1600 | 0.0271 | 0.2351 | |
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| 0.0243 | 7.41 | 1800 | 0.0272 | 0.2351 | |
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| 0.0225 | 8.23 | 2000 | 0.0272 | 0.2353 | |
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| 0.0206 | 9.05 | 2200 | 0.0267 | 0.2368 | |
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| 0.0187 | 9.88 | 2400 | 0.0260 | 0.2367 | |
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| 0.0173 | 10.7 | 2600 | 0.0256 | 0.2383 | |
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| 0.0161 | 11.52 | 2800 | 0.0260 | 0.2383 | |
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| 0.0153 | 12.35 | 3000 | 0.0257 | 0.2377 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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