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tmnam20/videberta-base_1024
videberta-base_1024 is a text classification model from tmnam20. 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. --
Downloads · 30 days
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From the Hugging Face model README
This model is a fine-tuned version of Fsoft-AIC/videberta-base 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 |
|---|---|---|---|---|
| 0.5982 | 0.1 | 50 | 0.6297 | 0.75 |
| 0.5505 | 0.21 | 100 | 0.5696 | 0.75 |
| 0.5838 | 0.31 | 150 | 0.5629 | 0.75 |
| 0.5925 | 0.41 | 200 | 0.5931 | 0.75 |
| 0.7003 | 0.52 | 250 | 0.5931 | 0.75 |
| 0.606 | 0.62 | 300 | 0.5931 | 0.75 |
| 0.6744 | 0.72 | 350 | 0.5931 | 0.75 |
| 0.6448 | 0.83 | 400 | 0.5931 | 0.75 |
| 0.7365 | 0.93 | 450 | 0.5931 | 0.75 |
| 0.6083 | 1.03 | 500 | 0.5931 | 0.75 |
| 0.6217 | 1.14 | 550 | 0.5931 | 0.75 |
| 0.642 | 1.24 | 600 | 0.5931 | 0.75 |
| 0.6433 | 1.34 | 650 | 0.5931 | 0.75 |
| 0.7497 | 1.45 | 700 | 0.5931 | 0.75 |
| 0.6385 | 1.55 | 750 | 0.5931 | 0.75 |
| 0.6581 | 1.65 | 800 | 0.5931 | 0.75 |
| 0.6201 | 1.76 | 850 | 0.5931 | 0.75 |
| 0.6424 | 1.86 | 900 | 0.5931 | 0.75 |
| 0.619 | 1.96 | 950 | 0.5931 | 0.75 |
| 0.6807 | 2.07 | 1000 | 0.5931 | 0.75 |