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haspeech_ita

Text Classification
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xlm-roberta
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haspeech_ita

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  1. README.md +13 -17
  2. model.safetensors +1 -1
  3. runs/Nov27_19-00-52_eee07ad15600/events.out.tfevents.1701111657.eee07ad15600.1142.0 +3 -0
  4. runs/Nov27_19-08-47_eee07ad15600/events.out.tfevents.1701112130.eee07ad15600.1142.1 +3 -0
  5. runs/Nov27_19-11-08_eee07ad15600/events.out.tfevents.1701112270.eee07ad15600.2832.0 +3 -0
  6. training_args.bin +1 -1
README.md CHANGED
@@ -1,5 +1,5 @@
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  ---
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- license: mit
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  base_model: MilaNLProc/hate-ita-xlm-r-large
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  tags:
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  - generated_from_trainer
@@ -8,10 +8,6 @@ metrics:
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  model-index:
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  - name: haspeech_ita
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  results: []
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- language:
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- - it
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- datasets:
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- - Paul/hatecheck-italian
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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
@@ -19,10 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # haspeech_ita
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- This model is a fine-tuned version of [MilaNLProc/hate-ita-xlm-r-large](https://huggingface.co/MilaNLProc/hate-ita-xlm-r-large)
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- on a dataset [Paul/hatecheck-italian](https://huggingface.co/datasets/Paul/hatecheck-italian).
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0030
 
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  - Accuracy: 0.9973
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  ## Model description
@@ -53,14 +49,14 @@ 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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- | 0.3538 | 0.48 | 100 | 0.2109 | 0.9241 |
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- | 0.18 | 0.96 | 200 | 0.1058 | 0.9783 |
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- | 0.0924 | 1.44 | 300 | 0.0618 | 0.9892 |
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- | 0.0948 | 1.92 | 400 | 0.0382 | 0.9892 |
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- | 0.0475 | 2.4 | 500 | 0.0607 | 0.9919 |
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- | 0.0572 | 2.88 | 600 | 0.0030 | 0.9973 |
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  ### Framework versions
@@ -68,4 +64,4 @@ The following hyperparameters were used during training:
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  - Transformers 4.35.2
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  - Pytorch 2.0.1
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  - Datasets 2.15.0
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- - Tokenizers 0.15.0
 
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  ---
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+ license: gpl-3.0
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  base_model: MilaNLProc/hate-ita-xlm-r-large
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  tags:
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  - generated_from_trainer
 
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  model-index:
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  - name: haspeech_ita
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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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  # haspeech_ita
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+ This model is a fine-tuned version of [MilaNLProc/hate-ita-xlm-r-large](https://huggingface.co/MilaNLProc/hate-ita-xlm-r-large) on an unknown dataset.
 
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0250
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+ - F1 Macro: 0.9966
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  - Accuracy: 0.9973
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  ## Model description
 
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | F1 Macro | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
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+ | 0.4001 | 0.48 | 100 | 0.1722 | 0.9198 | 0.9377 |
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+ | 0.1669 | 0.96 | 200 | 0.0355 | 0.9865 | 0.9892 |
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+ | 0.0824 | 1.44 | 300 | 0.0839 | 0.9864 | 0.9892 |
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+ | 0.0672 | 1.92 | 400 | 0.0277 | 0.9933 | 0.9946 |
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+ | 0.0761 | 2.4 | 500 | 0.0483 | 0.9933 | 0.9946 |
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+ | 0.0413 | 2.88 | 600 | 0.0250 | 0.9966 | 0.9973 |
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  ### Framework versions
 
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  - Transformers 4.35.2
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  - Pytorch 2.0.1
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  - Datasets 2.15.0
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+ - Tokenizers 0.15.0
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