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cuadron11/suicide-distilbert-original-5-5
suicide-distilbert-original-5-5 is a text classification model from cuadron11. 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. --
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.safetensors268 MB · 100%
From the Hugging Face model README
This model is a fine-tuned version of distilbert-base-uncased 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 | Fscore |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 10 | 1.6028 | {'accuracy': 0.31} | 0.0961 | 0.31 | 0.1467 |
| No log | 2.0 | 20 | 1.5911 | {'accuracy': 0.31} | 0.0961 | 0.31 | 0.1467 |
| No log | 3.0 | 30 | 1.5529 | {'accuracy': 0.31} | 0.0971 | 0.31 | 0.1478 |
| No log | 4.0 | 40 | 1.5191 | {'accuracy': 0.32} | 0.1532 | 0.32 | 0.2072 |
| No log | 5.0 | 50 | 1.4784 | {'accuracy': 0.35} | 0.1829 | 0.35 | 0.2343 |
| No log | 6.0 | 60 | 1.4951 | {'accuracy': 0.39} | 0.3290 | 0.39 | 0.2927 |
| No log | 7.0 | 70 | 1.5486 | {'accuracy': 0.35} | 0.2532 | 0.35 | 0.2676 |
| No log | 8.0 | 80 | 1.5740 | {'accuracy': 0.38} | 0.3537 | 0.38 | 0.3242 |
| No log | 9.0 | 90 | 1.6350 | {'accuracy': 0.37} | 0.3219 | 0.37 | 0.3439 |
| No log | 10.0 | 100 | 1.7061 | {'accuracy': 0.38} | 0.3253 | 0.38 | 0.3401 |
| No log | 11.0 | 110 | 1.7335 | {'accuracy': 0.37} | 0.3214 | 0.37 | 0.3430 |
| No log | 12.0 | 120 | 1.8224 | {'accuracy': 0.39} | 0.3332 | 0.39 | 0.3558 |
| No log | 13.0 | 130 | 1.8892 | {'accuracy': 0.37} | 0.3207 | 0.37 | 0.3414 |
| No log | 14.0 | 140 | 2.0359 | {'accuracy': 0.34} | 0.3092 | 0.34 | 0.3232 |
| No log | 15.0 | 150 | 2.0748 | {'accuracy': 0.36} | 0.4394 | 0.36 | 0.3411 |
| No log | 16.0 | 160 | 2.2032 | {'accuracy': 0.37} | 0.3182 | 0.37 | 0.3367 |
| No log | 17.0 | 170 | 2.2481 | {'accuracy': 0.34} | 0.2971 | 0.34 | 0.3141 |
| No log | 18.0 | 180 | 2.2278 | {'accuracy': 0.34} | 0.2957 | 0.34 | 0.3157 |
| No log | 19.0 | 190 | 2.2986 | {'accuracy': 0.32} | 0.2828 | 0.32 | 0.2981 |
| No log | 20.0 | 200 | 2.3097 | {'accuracy': 0.33} | 0.2925 | 0.33 | 0.3091 |