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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-end2end-questions-generation-cvqualtrics-squad-V1 |
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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-end2end-questions-generation-cvqualtrics-squad-V1 |
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## Model description |
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This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the Custom Domain-Specific dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2337 |
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### Framework versions |
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- Transformers 4.21.0 |
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- Pytorch 1.12.0+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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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: 0.0001 |
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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: 16 |
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- total_train_batch_size: 64 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 2.6162 | 0.34 | 100 | 1.8890 | |
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| 1.9995 | 0.67 | 200 | 1.6871 | |
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| 1.8697 | 1.01 | 300 | 1.6146 | |
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| 1.7682 | 1.34 | 400 | 1.5530 | |
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| 1.7323 | 1.68 | 500 | 1.5232 | |
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| 1.7256 | 2.01 | 600 | 1.4921 | |
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| 1.6506 | 2.35 | 700 | 1.4640 | |
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| 1.6438 | 2.68 | 800 | 1.4406 | |
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| 1.6399 | 3.02 | 900 | 1.4137 | |
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| 1.5786 | 3.36 | 1000 | 1.3924 | |
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| 1.5805 | 3.69 | 1100 | 1.3788 | |
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| 1.5824 | 4.03 | 1200 | 1.3626 | |
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| 1.5295 | 4.36 | 1300 | 1.3454 | |
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| 1.5333 | 4.7 | 1400 | 1.3356 | |
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| 1.537 | 5.03 | 1500 | 1.3230 | |
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| 1.5002 | 5.37 | 1600 | 1.3157 | |
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| 1.4936 | 5.7 | 1700 | 1.3046 | |
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| 1.4937 | 6.04 | 1800 | 1.2958 | |
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| 1.4649 | 6.38 | 1900 | 1.2826 | |
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| 1.4742 | 6.71 | 2000 | 1.2744 | |
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| 1.4641 | 7.05 | 2100 | 1.2603 | |
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| 1.4472 | 7.38 | 2200 | 1.2595 | |
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| 1.4403 | 7.72 | 2300 | 1.2526 | |
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| 1.4508 | 8.05 | 2400 | 1.2475 | |
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| 1.4191 | 8.39 | 2500 | 1.2412 | |
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| 1.4367 | 8.72 | 2600 | 1.2354 | |
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| 1.4272 | 9.06 | 2700 | 1.2386 | |
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| 1.4104 | 9.4 | 2800 | 1.2323 | |
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| 1.4179 | 9.73 | 2900 | 1.2337 | |
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