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Sairii
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comida_no_comida_text_classifier

Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
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Sairii commited on
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Sbudo text classifier

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  1. README.md +12 -12
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -18,8 +18,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0758
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- - Accuracy: 0.9799
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  ## Model description
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@@ -50,16 +50,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.5363 | 1.0 | 25 | 0.3316 | 0.8643 |
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- | 0.1659 | 2.0 | 50 | 0.1660 | 0.9497 |
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- | 0.0676 | 3.0 | 75 | 0.0218 | 0.9899 |
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- | 0.0248 | 4.0 | 100 | 0.0794 | 0.9749 |
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- | 0.0104 | 5.0 | 125 | 0.0263 | 0.9849 |
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- | 0.0021 | 6.0 | 150 | 0.0461 | 0.9749 |
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- | 0.0102 | 7.0 | 175 | 0.0494 | 0.9849 |
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- | 0.0006 | 8.0 | 200 | 0.0719 | 0.9799 |
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- | 0.0005 | 9.0 | 225 | 0.0755 | 0.9799 |
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- | 0.0005 | 10.0 | 250 | 0.0758 | 0.9799 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1424
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+ - Accuracy: 0.9698
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.4879 | 1.0 | 25 | 0.2264 | 0.9196 |
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+ | 0.1452 | 2.0 | 50 | 0.2094 | 0.9447 |
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+ | 0.0837 | 3.0 | 75 | 0.0876 | 0.9749 |
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+ | 0.0281 | 4.0 | 100 | 0.1444 | 0.9648 |
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+ | 0.0127 | 5.0 | 125 | 0.1225 | 0.9698 |
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+ | 0.0008 | 6.0 | 150 | 0.1622 | 0.9698 |
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+ | 0.0005 | 7.0 | 175 | 0.1584 | 0.9698 |
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+ | 0.0004 | 8.0 | 200 | 0.1448 | 0.9698 |
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+ | 0.0003 | 9.0 | 225 | 0.1428 | 0.9698 |
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+ | 0.0003 | 10.0 | 250 | 0.1424 | 0.9698 |
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  ### Framework versions
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