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gokuls/hBERTv2_new_pretrain_48_emb_com_wnli
hBERTv2_new_pretrain_48_emb_com_wnli is a text classification model from gokuls. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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From the Hugging Face model README
This model is a fine-tuned version of gokuls/bert_12_layer_model_v2_complete_training_new_emb_compress_48 on the GLUE WNLI 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 |
|---|---|---|---|---|
| 0.9415 | 1.0 | 5 | 0.7306 | 0.4366 |
| 0.7146 | 2.0 | 10 | 0.7870 | 0.4366 |
| 0.7207 | 3.0 | 15 | 0.7136 | 0.4225 |
| 0.6988 | 4.0 | 20 | 0.7277 | 0.4366 |
| 0.7058 | 5.0 | 25 | 0.7434 | 0.4366 |
| 0.7171 | 6.0 | 30 | 0.6963 | 0.4366 |
| 0.7007 | 7.0 | 35 | 0.6897 | 0.5634 |
| 0.7085 | 8.0 | 40 | 0.6900 | 0.5634 |
| 0.7282 | 9.0 | 45 | 0.6929 | 0.5634 |
| 0.695 | 10.0 | 50 | 0.6970 | 0.4366 |
| 0.6939 | 11.0 | 55 | 0.6868 | 0.5634 |
| 0.6955 | 12.0 | 60 | 0.6904 | 0.5634 |
| 0.6934 | 13.0 | 65 | 0.7015 | 0.4366 |
| 0.6974 | 14.0 | 70 | 0.6964 | 0.4366 |
| 0.695 | 15.0 | 75 | 0.6904 | 0.5634 |
| 0.7003 | 16.0 | 80 | 0.6981 | 0.4366 |