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Correkt/question_extractor_77m
question_extractor_77m is a machine learning model from Correkt. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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.safetensors308 MB · 99%
From the Hugging Face model README
This model is a fine-tuned version of google/flan-t5-small on the None dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.7133 | 0.0973 | 500 | 0.2155 |
| 0.1448 | 0.1945 | 1000 | 0.1211 |
| 0.1325 | 0.2918 | 1500 | 0.1143 |
| 0.1338 | 0.3890 | 2000 | 0.1098 |
| 0.1256 | 0.4863 | 2500 | 0.1073 |
| 0.1259 | 0.5835 | 3000 | 0.1051 |
| 0.1238 | 0.6808 | 3500 | 0.1034 |
| 0.1188 | 0.7781 | 4000 | 0.1025 |
| 0.1157 | 0.8753 | 4500 | 0.1007 |
| 0.1187 | 0.9726 | 5000 | 0.0998 |
| 0.1135 | 1.0698 | 5500 | 0.0990 |
| 0.1114 | 1.1671 | 6000 | 0.0985 |
| 0.1141 | 1.2643 | 6500 | 0.0973 |
| 0.1106 | 1.3616 | 7000 | 0.0969 |
| 0.1119 | 1.4589 | 7500 | 0.0962 |
| 0.1126 | 1.5561 | 8000 | 0.0961 |
| 0.1076 | 1.6534 | 8500 | 0.0955 |
| 0.1113 | 1.7506 | 9000 | 0.0951 |
| 0.1097 | 1.8479 | 9500 | 0.0947 |
| 0.1098 | 1.9451 | 10000 | 0.0943 |
| 0.1082 | 2.0424 | 10500 | 0.0941 |
| 0.1079 | 2.1397 | 11000 | 0.0939 |
| 0.1056 | 2.2369 | 11500 | 0.0938 |
| 0.1064 | 2.3342 | 12000 | 0.0936 |
| 0.1053 | 2.4314 | 12500 | 0.0933 |
| 0.1085 | 2.5287 | 13000 | 0.0931 |
| 0.1062 | 2.6259 | 13500 | 0.0931 |
| 0.1094 | 2.7232 | 14000 | 0.0929 |
| 0.1081 | 2.8205 | 14500 | 0.0930 |
| 0.1051 | 2.9177 | 15000 | 0.0930 |