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Anwaarma/MM05
MM05 is a text classification model from Anwaarma. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
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 prajjwal1/bert-tiny on an unknown 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 | F1 |
|---|---|---|---|---|---|
| No log | 0.0 | 50 | 0.6884 | 0.58 | 0.4258 |
| No log | 0.01 | 100 | 0.6988 | 0.42 | 0.2485 |
| No log | 0.01 | 150 | 0.6952 | 0.42 | 0.2485 |
| No log | 0.02 | 200 | 0.6886 | 0.58 | 0.4258 |
| No log | 0.02 | 250 | 0.6889 | 0.59 | 0.4481 |
| No log | 0.02 | 300 | 0.6920 | 0.59 | 0.5916 |
| No log | 0.03 | 350 | 0.6917 | 0.57 | 0.5535 |
| No log | 0.03 | 400 | 0.6947 | 0.45 | 0.3250 |
| No log | 0.04 | 450 | 0.6541 | 0.69 | 0.6866 |
| 0.6877 | 0.04 | 500 | 0.6117 | 0.7 | 0.6829 |
| 0.6877 | 0.04 | 550 | 0.5938 | 0.71 | 0.7030 |
| 0.6877 | 0.05 | 600 | 0.5851 | 0.74 | 0.7390 |
| 0.6877 | 0.05 | 650 | 0.5721 | 0.77 | 0.7645 |
| 0.6877 | 0.06 | 700 | 0.5612 | 0.77 | 0.7704 |
| 0.6877 | 0.06 | 750 | 0.5368 | 0.76 | 0.7612 |
| 0.6877 | 0.06 | 800 | 0.5013 | 0.77 | 0.7696 |
| 0.6877 | 0.07 | 850 | 0.4831 | 0.78 | 0.7792 |
| 0.6877 | 0.07 | 900 | 0.4831 | 0.78 | 0.7792 |
| 0.6877 | 0.08 | 950 | 0.4573 | 0.8 | 0.7886 |
| 0.5813 | 0.08 | 1000 | 0.4576 | 0.79 | 0.7792 |
| 0.5813 | 0.08 | 1050 | 0.4483 | 0.81 | 0.7956 |
| 0.5813 | 0.09 | 1100 | 0.4377 | 0.8 | 0.7886 |
| 0.5813 | 0.09 | 1150 | 0.4297 | 0.81 | 0.7956 |
| 0.5813 | 0.1 | 1200 | 0.4287 | 0.81 | 0.7956 |
| 0.5813 | 0.1 | 1250 | 0.4301 | 0.81 | 0.7956 |
| 0.5813 | 0.1 | 1300 | 0.4286 | 0.81 | 0.7956 |
| 0.5813 | 0.11 | 1350 | 0.4193 | 0.81 | 0.7956 |
| 0.5813 | 0.11 | 1400 | 0.4088 | 0.81 | 0.7956 |
| 0.5813 | 0.12 | 1450 | 0.4107 | 0.81 | 0.7956 |
| 0.4699 | 0.12 | 1500 | 0.4016 | 0.81 | 0.7956 |
| 0.4699 | 0.12 | 1550 | 0.4056 | 0.81 | 0.7956 |
| 0.4699 | 0.13 | 1600 | 0.4095 | 0.81 | 0.7956 |
| 0.4699 | 0.13 | 1650 | 0.3973 | 0.81 | 0.7956 |
| 0.4699 | 0.14 | 1700 | 0.3907 | 0.81 | 0.7956 |
| 0.4699 | 0.14 | 1750 | 0.3907 | 0.81 | 0.7956 |