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distilbert-base-uncased-finetuned-Multi_classification

Text Classification
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distilbert
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text-embeddings-inference
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update model card README.md

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@@ -16,14 +16,14 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.7153
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- - Accuracy: 0.2586
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- - Macro Averaged Precision: 0.1743
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- - Micro Averaged Precision: 0.2586
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- - Macro Averaged Recall: 0.2226
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- - Micro Averaged Recall: 0.2586
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- - Macro Averaged F1: 0.1773
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- - Micro Averaged F1: 0.2586
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro Averaged Precision | Micro Averaged Precision | Macro Averaged Recall | Micro Averaged Recall | Macro Averaged F1 | Micro Averaged F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------------------------:|:------------------------:|:---------------------:|:---------------------:|:-----------------:|:-----------------:|
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- | 1.7386 | 1.0 | 635 | 1.7153 | 0.2586 | 0.1743 | 0.2586 | 0.2226 | 0.2586 | 0.1773 | 0.2586 |
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- | 1.6671 | 2.0 | 1270 | 1.7172 | 0.2602 | 0.3079 | 0.2602 | 0.2492 | 0.2602 | 0.2231 | 0.2602 |
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- | 1.568 | 3.0 | 1905 | 1.7858 | 0.2648 | 0.3018 | 0.2648 | 0.2406 | 0.2648 | 0.2301 | 0.2648 |
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- | 1.2182 | 4.0 | 2540 | 1.9094 | 0.2648 | 0.2871 | 0.2648 | 0.2525 | 0.2648 | 0.2534 | 0.2648 |
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- | 0.9933 | 5.0 | 3175 | 2.1207 | 0.2672 | 0.2812 | 0.2672 | 0.2456 | 0.2672 | 0.2460 | 0.2672 |
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- | 0.8324 | 6.0 | 3810 | 2.3384 | 0.2633 | 0.2724 | 0.2633 | 0.2476 | 0.2633 | 0.2486 | 0.2633 |
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- | 0.6742 | 7.0 | 4445 | 2.5548 | 0.2648 | 0.2807 | 0.2648 | 0.2483 | 0.2648 | 0.2507 | 0.2648 |
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- | 0.4396 | 8.0 | 5080 | 2.7507 | 0.2586 | 0.2682 | 0.2586 | 0.2406 | 0.2586 | 0.2423 | 0.2586 |
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- | 0.3695 | 9.0 | 5715 | 2.9507 | 0.2578 | 0.2830 | 0.2578 | 0.2419 | 0.2578 | 0.2449 | 0.2578 |
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- | 0.3175 | 10.0 | 6350 | 2.9991 | 0.2594 | 0.2765 | 0.2594 | 0.2426 | 0.2594 | 0.2447 | 0.2594 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5588
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+ - Accuracy: 0.7266
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+ - Macro Averaged Precision: 0.6830
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+ - Micro Averaged Precision: 0.7266
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+ - Macro Averaged Recall: 0.5652
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+ - Micro Averaged Recall: 0.7266
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+ - Macro Averaged F1: 0.5513
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+ - Micro Averaged F1: 0.7266
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro Averaged Precision | Micro Averaged Precision | Macro Averaged Recall | Micro Averaged Recall | Macro Averaged F1 | Micro Averaged F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------------------------:|:------------------------:|:---------------------:|:---------------------:|:-----------------:|:-----------------:|
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+ | 0.5811 | 1.0 | 635 | 0.5745 | 0.7055 | 0.3527 | 0.7055 | 0.5 | 0.7055 | 0.4137 | 0.7055 |
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+ | 0.5467 | 2.0 | 1270 | 0.5588 | 0.7266 | 0.6830 | 0.7266 | 0.5652 | 0.7266 | 0.5513 | 0.7266 |
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+ | 0.4724 | 3.0 | 1905 | 0.6347 | 0.7109 | 0.6328 | 0.7109 | 0.5873 | 0.7109 | 0.5906 | 0.7109 |
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+ | 0.2379 | 4.0 | 2540 | 0.9110 | 0.7078 | 0.6281 | 0.7078 | 0.5874 | 0.7078 | 0.5910 | 0.7078 |
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+ | 0.1511 | 5.0 | 3175 | 1.2270 | 0.6953 | 0.6168 | 0.6953 | 0.5963 | 0.6953 | 0.6011 | 0.6953 |
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+ | 0.1074 | 6.0 | 3810 | 1.6106 | 0.7188 | 0.6470 | 0.7188 | 0.5859 | 0.7188 | 0.5875 | 0.7188 |
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+ | 0.0935 | 7.0 | 4445 | 1.8533 | 0.7070 | 0.6266 | 0.7070 | 0.5861 | 0.7070 | 0.5895 | 0.7070 |
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+ | 0.037 | 8.0 | 5080 | 2.0315 | 0.6875 | 0.6082 | 0.6875 | 0.5923 | 0.6875 | 0.5964 | 0.6875 |
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+ | 0.0294 | 9.0 | 5715 | 2.0726 | 0.7078 | 0.6295 | 0.7078 | 0.5928 | 0.7078 | 0.5975 | 0.7078 |
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+ | 0.0238 | 10.0 | 6350 | 2.1236 | 0.7086 | 0.6303 | 0.7086 | 0.5918 | 0.7086 | 0.5963 | 0.7086 |
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  ### Framework versions