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test7_balanced_and_sentence

Text Classification
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roberta
Generated from Trainer
text-embeddings-inference
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End of training

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  1. README.md +31 -31
  2. logs/events.out.tfevents.1711540488.c877f04894a5.278.2 +2 -2
  3. logs/events.out.tfevents.1711542852.c877f04894a5.278.3 +3 -0
  4. model.safetensors +1 -1
README.md CHANGED
@@ -15,7 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [ibaucells/RoBERTa-ca-CaWikiTC](https://huggingface.co/ibaucells/RoBERTa-ca-CaWikiTC) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.1090
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  ## Model description
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@@ -47,36 +47,36 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 2.8511 | 1.0 | 63 | 2.8392 |
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- | 2.8303 | 2.0 | 126 | 2.8357 |
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- | 2.8277 | 3.0 | 189 | 2.8396 |
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- | 2.7933 | 4.0 | 252 | 2.8123 |
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- | 2.7264 | 5.0 | 315 | 2.7844 |
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- | 2.6213 | 6.0 | 378 | 2.7200 |
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- | 2.513 | 7.0 | 441 | 2.7099 |
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- | 2.4436 | 8.0 | 504 | 2.5845 |
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- | 2.0946 | 9.0 | 567 | 2.5724 |
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- | 1.9708 | 10.0 | 630 | 2.3567 |
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- | 1.6289 | 11.0 | 693 | 2.3670 |
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- | 1.5015 | 12.0 | 756 | 2.3716 |
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- | 1.3488 | 13.0 | 819 | 2.1432 |
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- | 1.0815 | 14.0 | 882 | 2.2774 |
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- | 0.9128 | 15.0 | 945 | 2.3228 |
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- | 0.7779 | 16.0 | 1008 | 2.2310 |
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- | 0.5918 | 17.0 | 1071 | 2.3602 |
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- | 0.5215 | 18.0 | 1134 | 2.3472 |
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- | 0.3969 | 19.0 | 1197 | 2.3990 |
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- | 0.421 | 20.0 | 1260 | 2.4948 |
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- | 0.2811 | 21.0 | 1323 | 2.6314 |
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- | 0.2538 | 22.0 | 1386 | 2.7452 |
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- | 0.1646 | 23.0 | 1449 | 2.7550 |
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- | 0.1553 | 24.0 | 1512 | 2.8536 |
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- | 0.1743 | 25.0 | 1575 | 2.8543 |
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- | 0.198 | 26.0 | 1638 | 2.9044 |
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- | 0.1065 | 27.0 | 1701 | 2.9262 |
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- | 0.0935 | 28.0 | 1764 | 2.8968 |
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- | 0.0972 | 29.0 | 1827 | 2.9331 |
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- | 0.1296 | 30.0 | 1890 | 2.9396 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [ibaucells/RoBERTa-ca-CaWikiTC](https://huggingface.co/ibaucells/RoBERTa-ca-CaWikiTC) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.7381
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 2.8474 | 1.0 | 63 | 2.8422 |
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+ | 2.8221 | 2.0 | 126 | 2.8406 |
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+ | 2.8228 | 3.0 | 189 | 2.8483 |
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+ | 2.7804 | 4.0 | 252 | 2.8079 |
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+ | 2.6707 | 5.0 | 315 | 2.7224 |
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+ | 2.5542 | 6.0 | 378 | 2.6884 |
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+ | 2.3782 | 7.0 | 441 | 2.5568 |
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+ | 2.302 | 8.0 | 504 | 2.5003 |
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+ | 1.9717 | 9.0 | 567 | 2.2786 |
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+ | 1.7659 | 10.0 | 630 | 2.1437 |
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+ | 1.4552 | 11.0 | 693 | 2.0261 |
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+ | 1.1394 | 12.0 | 756 | 1.8772 |
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+ | 0.8644 | 13.0 | 819 | 1.8367 |
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+ | 0.826 | 14.0 | 882 | 1.6980 |
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+ | 0.5626 | 15.0 | 945 | 1.8251 |
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+ | 0.3684 | 16.0 | 1008 | 1.8207 |
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+ | 0.2861 | 17.0 | 1071 | 2.0102 |
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+ | 0.2056 | 18.0 | 1134 | 2.2188 |
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+ | 0.1174 | 19.0 | 1197 | 2.1110 |
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+ | 0.1485 | 20.0 | 1260 | 2.1932 |
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+ | 0.1064 | 21.0 | 1323 | 2.2119 |
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+ | 0.065 | 22.0 | 1386 | 2.3062 |
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+ | 0.0528 | 23.0 | 1449 | 2.3949 |
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+ | 0.0734 | 24.0 | 1512 | 2.3761 |
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+ | 0.0342 | 25.0 | 1575 | 2.4951 |
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+ | 0.0686 | 26.0 | 1638 | 2.5017 |
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+ | 0.0281 | 27.0 | 1701 | 2.5199 |
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+ | 0.0262 | 28.0 | 1764 | 2.5461 |
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+ | 0.0346 | 29.0 | 1827 | 2.5469 |
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+ | 0.0261 | 30.0 | 1890 | 2.5541 |
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  ### Framework versions
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