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sakren
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debert-imeocap

Text Classification
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deberta-v2
Generated from Trainer
text-embeddings-inference
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sakren/debert-imeocap

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  1. README.md +20 -20
  2. model.safetensors +1 -1
  3. runs/May15_18-08-01_95a092faa389/events.out.tfevents.1715796514.95a092faa389.35.9 +2 -2
  4. runs/May15_18-08-01_95a092faa389/events.out.tfevents.1715797115.95a092faa389.35.10 +3 -0
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.3914
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- - F1: 0.6372
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- - Precision: 0.6448
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- - Recall: 0.6365
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- - Accuracy: 0.6365
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  ## Model description
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@@ -55,21 +55,21 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|:--------:|
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- | 1.5405 | 1.0 | 74 | 1.4488 | 0.3206 | 0.2386 | 0.4885 | 0.4885 |
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- | 1.3156 | 2.0 | 148 | 1.1964 | 0.5541 | 0.5627 | 0.575 | 0.575 |
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- | 1.0728 | 3.0 | 222 | 1.1077 | 0.6001 | 0.6189 | 0.5981 | 0.5981 |
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- | 0.9239 | 4.0 | 296 | 1.0742 | 0.6324 | 0.6361 | 0.6365 | 0.6365 |
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- | 0.7802 | 5.0 | 370 | 1.0834 | 0.6073 | 0.6333 | 0.6058 | 0.6058 |
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- | 0.661 | 6.0 | 444 | 1.1733 | 0.5984 | 0.6166 | 0.5962 | 0.5962 |
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- | 0.602 | 7.0 | 518 | 1.1786 | 0.5911 | 0.6193 | 0.5885 | 0.5885 |
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- | 0.5391 | 8.0 | 592 | 1.2171 | 0.6156 | 0.6251 | 0.6154 | 0.6154 |
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- | 0.4815 | 9.0 | 666 | 1.2566 | 0.6259 | 0.6399 | 0.625 | 0.625 |
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- | 0.4548 | 10.0 | 740 | 1.2927 | 0.6233 | 0.6417 | 0.6212 | 0.6212 |
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- | 0.4538 | 11.0 | 814 | 1.2969 | 0.6385 | 0.6461 | 0.6385 | 0.6385 |
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- | 0.4119 | 12.0 | 888 | 1.3455 | 0.6376 | 0.6464 | 0.6365 | 0.6365 |
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- | 0.3968 | 13.0 | 962 | 1.3709 | 0.6304 | 0.6413 | 0.6288 | 0.6288 |
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- | 0.352 | 14.0 | 1036 | 1.3823 | 0.6246 | 0.6360 | 0.6231 | 0.6231 |
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- | 0.3551 | 15.0 | 1110 | 1.3914 | 0.6372 | 0.6448 | 0.6365 | 0.6365 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.8660
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+ - F1: 0.6185
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+ - Precision: 0.6337
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+ - Recall: 0.6154
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+ - Accuracy: 0.6154
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|:--------:|
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+ | 0.4637 | 1.0 | 74 | 1.3864 | 0.6129 | 0.6262 | 0.6115 | 0.6115 |
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+ | 0.3815 | 2.0 | 148 | 1.3801 | 0.6193 | 0.6348 | 0.6173 | 0.6173 |
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+ | 0.3363 | 3.0 | 222 | 1.6944 | 0.6077 | 0.6297 | 0.6077 | 0.6077 |
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+ | 0.31 | 4.0 | 296 | 1.6945 | 0.5995 | 0.6285 | 0.5942 | 0.5942 |
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+ | 0.2885 | 5.0 | 370 | 1.5945 | 0.6218 | 0.6306 | 0.6192 | 0.6192 |
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+ | 0.2594 | 6.0 | 444 | 1.7662 | 0.6279 | 0.6396 | 0.625 | 0.625 |
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+ | 0.2319 | 7.0 | 518 | 1.7093 | 0.6210 | 0.6321 | 0.6173 | 0.6173 |
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+ | 0.2306 | 8.0 | 592 | 1.8068 | 0.6279 | 0.6341 | 0.6288 | 0.6288 |
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+ | 0.2167 | 9.0 | 666 | 1.7306 | 0.6376 | 0.6444 | 0.6346 | 0.6346 |
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+ | 0.2158 | 10.0 | 740 | 1.8745 | 0.6262 | 0.6318 | 0.6269 | 0.6269 |
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+ | 0.222 | 11.0 | 814 | 1.8323 | 0.6200 | 0.6348 | 0.6173 | 0.6173 |
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+ | 0.2152 | 12.0 | 888 | 1.8576 | 0.6246 | 0.6363 | 0.6212 | 0.6212 |
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+ | 0.226 | 13.0 | 962 | 1.8880 | 0.6343 | 0.6411 | 0.6308 | 0.6308 |
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+ | 0.2097 | 14.0 | 1036 | 1.8884 | 0.6152 | 0.6326 | 0.6115 | 0.6115 |
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+ | 0.2192 | 15.0 | 1110 | 1.8660 | 0.6185 | 0.6337 | 0.6154 | 0.6154 |
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  ### Framework versions
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