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roberta-suicide-detection-hk

Text Classification
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xlm-roberta
Generated from Trainer
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  1. README.md +39 -39
  2. runs/May29_10-15-34_d69883b8441d/events.out.tfevents.1716977735.d69883b8441d.34.0 +2 -2
README.md CHANGED
@@ -1,24 +1,24 @@
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  ---
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- license: cc-by-4.0
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- base_model: indiejoseph/bert-base-cantonese
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  tags:
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  - generated_from_trainer
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  metrics:
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  - accuracy
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  model-index:
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- - name: bert-suicide-detection-hk
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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- # bert-suicide-detection-hk
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- This model is a fine-tuned version of [indiejoseph/bert-base-cantonese](https://huggingface.co/indiejoseph/bert-base-cantonese) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0002
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- - Accuracy: 1.0
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  ## Model description
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@@ -47,40 +47,40 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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- |:-------------:|:------:|:----:|:---------------:|:--------:|
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- | 0.3468 | 0.1852 | 20 | 0.2052 | 0.9020 |
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- | 0.2089 | 0.3704 | 40 | 0.1276 | 0.9216 |
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- | 0.214 | 0.5556 | 60 | 0.0251 | 0.9804 |
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- | 0.0807 | 0.7407 | 80 | 0.0165 | 0.9804 |
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- | 0.1064 | 0.9259 | 100 | 0.0031 | 1.0 |
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- | 0.0134 | 1.1111 | 120 | 0.0025 | 1.0 |
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- | 0.0349 | 1.2963 | 140 | 0.0007 | 1.0 |
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- | 0.0819 | 1.4815 | 160 | 0.0706 | 0.9608 |
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- | 0.0586 | 1.6667 | 180 | 0.0005 | 1.0 |
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- | 0.0368 | 1.8519 | 200 | 0.0005 | 1.0 |
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- | 0.0485 | 2.0370 | 220 | 0.0031 | 1.0 |
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- | 0.017 | 2.2222 | 240 | 0.0003 | 1.0 |
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- | 0.0017 | 2.4074 | 260 | 0.0021 | 1.0 |
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- | 0.0004 | 2.5926 | 280 | 0.0004 | 1.0 |
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- | 0.0444 | 2.7778 | 300 | 0.0003 | 1.0 |
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- | 0.0005 | 2.9630 | 320 | 0.0003 | 1.0 |
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- | 0.0003 | 3.1481 | 340 | 0.0002 | 1.0 |
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- | 0.0238 | 3.3333 | 360 | 0.0003 | 1.0 |
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- | 0.0003 | 3.5185 | 380 | 0.0002 | 1.0 |
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- | 0.0003 | 3.7037 | 400 | 0.0002 | 1.0 |
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- | 0.0003 | 3.8889 | 420 | 0.0002 | 1.0 |
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- | 0.0007 | 4.0741 | 440 | 0.0002 | 1.0 |
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- | 0.0002 | 4.2593 | 460 | 0.0002 | 1.0 |
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- | 0.0003 | 4.4444 | 480 | 0.0002 | 1.0 |
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- | 0.0002 | 4.6296 | 500 | 0.0002 | 1.0 |
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- | 0.0002 | 4.8148 | 520 | 0.0002 | 1.0 |
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- | 0.0002 | 5.0 | 540 | 0.0002 | 1.0 |
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  ### Framework versions
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- - Transformers 4.41.1
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  - Pytorch 2.1.2
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- - Datasets 2.19.1
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- - Tokenizers 0.19.1
 
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  ---
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+ license: mit
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+ base_model: FacebookAI/xlm-roberta-large
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  tags:
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  - generated_from_trainer
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  metrics:
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  - accuracy
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  model-index:
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+ - name: roberta-suicide-detection-hk
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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+ # roberta-suicide-detection-hk
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+ This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1628
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+ - Accuracy: 0.9608
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.6783 | 0.19 | 20 | 0.5885 | 0.7451 |
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+ | 0.7304 | 0.37 | 40 | 0.6978 | 0.7059 |
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+ | 0.6086 | 0.56 | 60 | 0.4823 | 0.7255 |
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+ | 0.5071 | 0.74 | 80 | 0.5564 | 0.7059 |
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+ | 0.5933 | 0.93 | 100 | 0.5993 | 0.6667 |
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+ | 0.6311 | 1.11 | 120 | 0.6531 | 0.7059 |
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+ | 0.5867 | 1.3 | 140 | 0.6158 | 0.4510 |
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+ | 0.6845 | 1.48 | 160 | 0.5851 | 0.7059 |
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+ | 0.7479 | 1.67 | 180 | 0.6134 | 0.7059 |
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+ | 0.573 | 1.85 | 200 | 0.5972 | 0.7059 |
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+ | 0.6183 | 2.04 | 220 | 0.5631 | 0.7059 |
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+ | 0.657 | 2.22 | 240 | 0.6166 | 0.7059 |
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+ | 0.7293 | 2.41 | 260 | 0.5851 | 0.7059 |
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+ | 0.6215 | 2.59 | 280 | 0.4603 | 0.7647 |
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+ | 0.3509 | 2.78 | 300 | 0.6292 | 0.7647 |
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+ | 0.3484 | 2.96 | 320 | 0.6770 | 0.8431 |
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+ | 0.3279 | 3.15 | 340 | 0.1123 | 0.9608 |
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+ | 0.4096 | 3.33 | 360 | 0.1380 | 0.9804 |
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+ | 0.3626 | 3.52 | 380 | 0.4317 | 0.9216 |
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+ | 0.2809 | 3.7 | 400 | 0.1681 | 0.9804 |
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+ | 0.5547 | 3.89 | 420 | 0.1194 | 0.9804 |
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+ | 0.3751 | 4.07 | 440 | 0.2943 | 0.9216 |
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+ | 0.1131 | 4.26 | 460 | 0.0558 | 0.9804 |
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+ | 0.182 | 4.44 | 480 | 0.1463 | 0.9608 |
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+ | 0.2991 | 4.63 | 500 | 0.2800 | 0.9608 |
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+ | 0.2471 | 4.81 | 520 | 0.2261 | 0.9608 |
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+ | 0.1022 | 5.0 | 540 | 0.1628 | 0.9608 |
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  ### Framework versions
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+ - Transformers 4.39.3
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  - Pytorch 2.1.2
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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