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Waynehills-NLP-doogie

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PyTorch
TensorBoard
t5
text2text-generation
Generated from Trainer
text-generation-inference
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+ ---
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: Waynehills-NLP-doogie
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+ results: []
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+ ---
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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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+
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+ # Waynehills-NLP-doogie
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+
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+ This model is a fine-tuned version of [KETI-AIR/ke-t5-base-ko](https://huggingface.co/KETI-AIR/ke-t5-base-ko) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.9188
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 2
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+ - eval_batch_size: 2
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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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+ - lr_scheduler_warmup_steps: 10
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+ - num_epochs: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:-----:|:---------------:|
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+ | 28.2167 | 0.06 | 1000 | 9.7030 |
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+ | 10.4479 | 0.12 | 2000 | 7.5450 |
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+ | 8.0306 | 0.19 | 3000 | 6.1969 |
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+ | 6.503 | 0.25 | 4000 | 5.3015 |
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+ | 5.5406 | 0.31 | 5000 | 4.6363 |
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+ | 4.7299 | 0.38 | 6000 | 4.0431 |
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+ | 3.9263 | 0.44 | 7000 | 3.6313 |
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+ | 3.4111 | 0.5 | 8000 | 3.4830 |
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+ | 3.0517 | 0.56 | 9000 | 3.3294 |
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+ | 2.7524 | 0.62 | 10000 | 3.2077 |
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+ | 2.5402 | 0.69 | 11000 | 3.1094 |
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+ | 2.3228 | 0.75 | 12000 | 3.1099 |
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+ | 2.1513 | 0.81 | 13000 | 3.0284 |
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+ | 2.0418 | 0.88 | 14000 | 3.0155 |
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+ | 1.8875 | 0.94 | 15000 | 3.0241 |
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+ | 1.756 | 1.0 | 16000 | 3.0165 |
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+ | 1.6489 | 1.06 | 17000 | 2.9849 |
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+ | 1.5788 | 1.12 | 18000 | 2.9496 |
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+ | 1.5368 | 1.19 | 19000 | 2.9500 |
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+ | 1.4467 | 1.25 | 20000 | 3.0133 |
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+ | 1.381 | 1.31 | 21000 | 2.9631 |
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+ | 1.3451 | 1.38 | 22000 | 3.0159 |
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+ | 1.2917 | 1.44 | 23000 | 2.9906 |
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+ | 1.2605 | 1.5 | 24000 | 3.0006 |
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+ | 1.2003 | 1.56 | 25000 | 2.9797 |
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+ | 1.1987 | 1.62 | 26000 | 2.9253 |
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+ | 1.1703 | 1.69 | 27000 | 3.0044 |
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+ | 1.1474 | 1.75 | 28000 | 2.9216 |
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+ | 1.0816 | 1.81 | 29000 | 2.9645 |
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+ | 1.0709 | 1.88 | 30000 | 3.0439 |
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+ | 1.0476 | 1.94 | 31000 | 3.0844 |
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+ | 1.0645 | 2.0 | 32000 | 2.9434 |
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+ | 1.0204 | 2.06 | 33000 | 2.9386 |
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+ | 0.9901 | 2.12 | 34000 | 3.0452 |
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+ | 0.9911 | 2.19 | 35000 | 2.9798 |
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+ | 0.9706 | 2.25 | 36000 | 2.9919 |
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+ | 0.9461 | 2.31 | 37000 | 3.0279 |
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+ | 0.9577 | 2.38 | 38000 | 2.9615 |
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+ | 0.9466 | 2.44 | 39000 | 2.9988 |
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+ | 0.9486 | 2.5 | 40000 | 2.9133 |
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+ | 0.9201 | 2.56 | 41000 | 3.0004 |
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+ | 0.896 | 2.62 | 42000 | 2.9626 |
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+ | 0.8893 | 2.69 | 43000 | 2.9667 |
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+ | 0.9028 | 2.75 | 44000 | 2.9543 |
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+ | 0.897 | 2.81 | 45000 | 2.8760 |
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+ | 0.8664 | 2.88 | 46000 | 2.9894 |
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+ | 0.8719 | 2.94 | 47000 | 2.8456 |
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+ | 0.8491 | 3.0 | 48000 | 2.9713 |
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+ | 0.8402 | 3.06 | 49000 | 2.9738 |
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+ | 0.8484 | 3.12 | 50000 | 2.9361 |
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+ | 0.8304 | 3.19 | 51000 | 2.8945 |
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+ | 0.8208 | 3.25 | 52000 | 2.9625 |
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+ | 0.8074 | 3.31 | 53000 | 3.0054 |
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+ | 0.8226 | 3.38 | 54000 | 2.9405 |
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+ | 0.8185 | 3.44 | 55000 | 2.9047 |
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+ | 0.8352 | 3.5 | 56000 | 2.9016 |
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+ | 0.8289 | 3.56 | 57000 | 2.9490 |
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+ | 0.7918 | 3.62 | 58000 | 2.9621 |
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+ | 0.8212 | 3.69 | 59000 | 2.9341 |
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+ | 0.7955 | 3.75 | 60000 | 2.9167 |
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+ | 0.7724 | 3.81 | 61000 | 2.9409 |
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+ | 0.8169 | 3.88 | 62000 | 2.8925 |
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+ | 0.7862 | 3.94 | 63000 | 2.9314 |
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+ | 0.803 | 4.0 | 64000 | 2.9271 |
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+ | 0.7595 | 4.06 | 65000 | 2.9263 |
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+ | 0.7931 | 4.12 | 66000 | 2.9400 |
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+ | 0.7759 | 4.19 | 67000 | 2.9501 |
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+ | 0.7859 | 4.25 | 68000 | 2.9133 |
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+ | 0.805 | 4.31 | 69000 | 2.8785 |
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+ | 0.7649 | 4.38 | 70000 | 2.9060 |
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+ | 0.7692 | 4.44 | 71000 | 2.8868 |
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+ | 0.7692 | 4.5 | 72000 | 2.9045 |
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+ | 0.7798 | 4.56 | 73000 | 2.8951 |
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+ | 0.7812 | 4.62 | 74000 | 2.9068 |
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+ | 0.7533 | 4.69 | 75000 | 2.9129 |
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+ | 0.7527 | 4.75 | 76000 | 2.9157 |
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+ | 0.7652 | 4.81 | 77000 | 2.9053 |
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+ | 0.7633 | 4.88 | 78000 | 2.9190 |
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+ | 0.7437 | 4.94 | 79000 | 2.9251 |
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+ | 0.7653 | 5.0 | 80000 | 2.9188 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.12.5
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+ - Pytorch 1.10.0+cu111
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+ - Datasets 1.5.0
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+ - Tokenizers 0.10.3