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lenatr99
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fine_tuned_cb_croslo

Text Classification
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bert
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fine_tuned_cb_croslo

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  1. README.md +10 -10
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -18,9 +18,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [EMBEDDIA/crosloengual-bert](https://huggingface.co/EMBEDDIA/crosloengual-bert) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.2679
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  - Accuracy: 0.6818
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- - F1: 0.6488
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  ## Model description
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@@ -51,14 +51,14 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
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- | 0.6412 | 3.5714 | 50 | 1.2351 | 0.3182 | 0.1536 |
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- | 0.2271 | 7.1429 | 100 | 0.9940 | 0.5455 | 0.4896 |
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- | 0.0176 | 10.7143 | 150 | 1.0287 | 0.6818 | 0.6313 |
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- | 0.0031 | 14.2857 | 200 | 1.1287 | 0.6818 | 0.6313 |
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- | 0.002 | 17.8571 | 250 | 1.1967 | 0.6818 | 0.6488 |
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- | 0.0015 | 21.4286 | 300 | 1.2596 | 0.6818 | 0.6488 |
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- | 0.0013 | 25.0 | 350 | 1.2666 | 0.6818 | 0.6488 |
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- | 0.0013 | 28.5714 | 400 | 1.2679 | 0.6818 | 0.6488 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [EMBEDDIA/crosloengual-bert](https://huggingface.co/EMBEDDIA/crosloengual-bert) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.3249
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  - Accuracy: 0.6818
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+ - F1: 0.6390
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
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+ | 0.7054 | 3.5714 | 50 | 1.4024 | 0.3182 | 0.1536 |
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+ | 0.3117 | 7.1429 | 100 | 1.0030 | 0.6818 | 0.6383 |
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+ | 0.0286 | 10.7143 | 150 | 1.0108 | 0.7273 | 0.6791 |
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+ | 0.0038 | 14.2857 | 200 | 1.1886 | 0.6818 | 0.6390 |
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+ | 0.0025 | 17.8571 | 250 | 1.2342 | 0.6818 | 0.6390 |
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+ | 0.0019 | 21.4286 | 300 | 1.2576 | 0.7273 | 0.6791 |
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+ | 0.0015 | 25.0 | 350 | 1.2963 | 0.6818 | 0.6390 |
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+ | 0.0015 | 28.5714 | 400 | 1.3249 | 0.6818 | 0.6390 |
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  ### Framework versions
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