Downloads · 30 days
12
5% of all-time downloads
rishavranaut/flanT5_large_MT
flanT5_large_MT is a text classification model from rishavranaut. Use it when you need a label for a piece of text. 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. --
Downloads · 30 days
12
5% of all-time downloads
All-time downloads
244
Public
Parameters
751M
78.1 GB on disk
Likes
0
Public
Click a slice to open those files.
.safetensors3 GB · 100%
From the Hugging Face model README
This model is a fine-tuned version of google/flan-t5-large 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 | Accuracy | Precision | Recall | F1 score |
|---|---|---|---|---|---|---|---|
| 1.2742 | 0.3910 | 2500 | 1.6400 | 0.69 | 0.7096 | 0.6433 | 0.6748 |
| 1.2294 | 0.7820 | 5000 | 0.9952 | 0.725 | 0.7872 | 0.6167 | 0.6916 |
| 1.0532 | 1.1730 | 7500 | 1.1585 | 0.69 | 0.6875 | 0.6967 | 0.6921 |
| 0.9314 | 1.5640 | 10000 | 0.8117 | 0.7417 | 0.7580 | 0.71 | 0.7332 |
| 0.8698 | 1.9550 | 12500 | 0.7872 | 0.7367 | 0.7817 | 0.6567 | 0.7138 |
| 0.7603 | 2.3459 | 15000 | 0.9449 | 0.77 | 0.7470 | 0.8167 | 0.7803 |
| 0.7207 | 2.7369 | 17500 | 0.9339 | 0.7917 | 0.7850 | 0.8033 | 0.7941 |
| 0.6447 | 3.1279 | 20000 | 1.0756 | 0.8017 | 0.8198 | 0.7733 | 0.7959 |
| 0.5358 | 3.5189 | 22500 | 1.0722 | 0.79 | 0.7788 | 0.81 | 0.7941 |
| 0.5169 | 3.9099 | 25000 | 1.0001 | 0.8067 | 0.8407 | 0.7567 | 0.7965 |
| 0.4011 | 4.3009 | 27500 | 1.0915 | 0.805 | 0.8144 | 0.79 | 0.8020 |
| 0.3177 | 4.6919 | 30000 | 1.2966 | 0.8083 | 0.8157 | 0.7967 | 0.8061 |
| 0.2783 | 5.0829 | 32500 | 1.2640 | 0.8117 | 0.7913 | 0.8467 | 0.8180 |
| 0.1352 | 5.4739 | 35000 | 1.3695 | 0.82 | 0.8333 | 0.8 | 0.8163 |
| 0.2168 | 5.8649 | 37500 | 1.3541 | 0.8133 | 0.8287 | 0.79 | 0.8089 |
| 0.1186 | 6.2559 | 40000 | 1.4063 | 0.8167 | 0.8276 | 0.8 | 0.8136 |
| 0.1205 | 6.6469 | 42500 | 1.6920 | 0.8033 | 0.7993 | 0.81 | 0.8046 |
| 0.0957 | 7.0378 | 45000 | 1.5681 | 0.815 | 0.8225 | 0.8033 | 0.8128 |
| 0.0406 | 7.4288 | 47500 | 1.9015 | 0.8083 | 0.8269 | 0.78 | 0.8027 |
| 0.0558 | 7.8198 | 50000 | 1.8359 | 0.8017 | 0.7967 | 0.81 | 0.8033 |
| 0.0549 | 8.2108 | 52500 | 1.8649 | 0.8083 | 0.8201 | 0.79 | 0.8048 |
| 0.0515 | 8.6018 | 55000 | 1.8556 | 0.8067 | 0.7949 | 0.8267 | 0.8105 |
| 0.0378 | 8.9928 | 57500 | 1.9273 | 0.7983 | 0.7806 | 0.83 | 0.8045 |
| 0.0182 | 9.3838 | 60000 | 1.9497 | 0.8133 | 0.8287 | 0.79 | 0.8089 |
| 0.0264 | 9.7748 | 62500 | 1.9444 | 0.815 | 0.8339 | 0.7867 | 0.8096 |