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peft-finetune-flan-t5-mc-question-generation

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  1. README.md +34 -18
README.md CHANGED
@@ -15,7 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.1553
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  ## Model description
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@@ -42,32 +42,48 @@ The following hyperparameters were used during training:
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  - total_train_batch_size: 32
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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: 2
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 2.2947 | 0.13 | 100 | 1.7430 |
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- | 1.8174 | 0.25 | 200 | 1.3561 |
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- | 1.5218 | 0.38 | 300 | 1.2409 |
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- | 1.4277 | 0.51 | 400 | 1.2068 |
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- | 1.3855 | 0.64 | 500 | 1.1918 |
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- | 1.3648 | 0.76 | 600 | 1.1808 |
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- | 1.3438 | 0.89 | 700 | 1.1744 |
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- | 1.3408 | 1.02 | 800 | 1.1685 |
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- | 1.3357 | 1.15 | 900 | 1.1658 |
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- | 1.3258 | 1.27 | 1000 | 1.1620 |
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- | 1.3187 | 1.4 | 1100 | 1.1597 |
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- | 1.3195 | 1.53 | 1200 | 1.1577 |
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- | 1.3168 | 1.65 | 1300 | 1.1572 |
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- | 1.3167 | 1.78 | 1400 | 1.1559 |
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- | 1.311 | 1.91 | 1500 | 1.1553 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.32.0
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  - Pytorch 2.0.0
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  - Datasets 2.1.0
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  - Tokenizers 0.13.3
 
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  This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.1306
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  ## Model description
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  - total_train_batch_size: 32
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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: 4
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 2.2907 | 0.13 | 100 | 1.7315 |
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+ | 1.8012 | 0.25 | 200 | 1.3366 |
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+ | 1.5077 | 0.38 | 300 | 1.2346 |
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+ | 1.419 | 0.51 | 400 | 1.2027 |
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+ | 1.3772 | 0.64 | 500 | 1.1884 |
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+ | 1.3566 | 0.76 | 600 | 1.1770 |
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+ | 1.3348 | 0.89 | 700 | 1.1696 |
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+ | 1.3307 | 1.02 | 800 | 1.1624 |
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+ | 1.3247 | 1.15 | 900 | 1.1586 |
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+ | 1.3139 | 1.27 | 1000 | 1.1537 |
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+ | 1.3048 | 1.4 | 1100 | 1.1507 |
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+ | 1.3045 | 1.53 | 1200 | 1.1476 |
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+ | 1.2999 | 1.65 | 1300 | 1.1451 |
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+ | 1.2978 | 1.78 | 1400 | 1.1425 |
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+ | 1.2903 | 1.91 | 1500 | 1.1407 |
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+ | 1.2897 | 2.04 | 1600 | 1.1409 |
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+ | 1.2881 | 2.16 | 1700 | 1.1386 |
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+ | 1.2845 | 2.29 | 1800 | 1.1374 |
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+ | 1.2749 | 2.42 | 1900 | 1.1360 |
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+ | 1.2846 | 2.55 | 2000 | 1.1349 |
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+ | 1.281 | 2.67 | 2100 | 1.1339 |
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+ | 1.282 | 2.8 | 2200 | 1.1331 |
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+ | 1.2786 | 2.93 | 2300 | 1.1326 |
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+ | 1.2799 | 3.06 | 2400 | 1.1322 |
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+ | 1.2777 | 3.18 | 2500 | 1.1320 |
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+ | 1.2767 | 3.31 | 2600 | 1.1316 |
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+ | 1.2716 | 3.44 | 2700 | 1.1313 |
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+ | 1.2762 | 3.56 | 2800 | 1.1309 |
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+ | 1.2723 | 3.69 | 2900 | 1.1305 |
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+ | 1.2741 | 3.82 | 3000 | 1.1304 |
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+ | 1.2762 | 3.95 | 3100 | 1.1306 |
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  ### Framework versions
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+ - Transformers 4.33.1
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  - Pytorch 2.0.0
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  - Datasets 2.1.0
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  - Tokenizers 0.13.3