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intent_analysis-3label-xml

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clasificador_xml_10ep

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  1. README.md +2 -14
  2. model.safetensors +1 -1
  3. runs/Nov13_15-14-53_2e415f38b8b6/events.out.tfevents.1731510900.2e415f38b8b6.1600.4 +3 -0
  4. runs/Nov13_15-17-34_2e415f38b8b6/events.out.tfevents.1731511060.2e415f38b8b6.1600.5 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -4,11 +4,6 @@ license: mit
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  base_model: xlm-roberta-base
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  tags:
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  - generated_from_trainer
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- metrics:
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- - accuracy
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- - precision
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- - recall
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- - f1
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  model-index:
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  - name: intent_analysis
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  results: []
@@ -20,12 +15,6 @@ should probably proofread and complete it, then remove this comment. -->
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  # intent_analysis
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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
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- It achieves the following results on the evaluation set:
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- - Loss: 0.0840
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- - Accuracy: 0.9871
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- - Precision: 0.9873
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- - Recall: 0.9872
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- - F1: 0.9872
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  ## Model description
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@@ -50,14 +39,13 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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- - num_epochs: 2
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | No log | 1.0 | 280 | 0.0849 | 0.9843 | 0.9846 | 0.9843 | 0.9843 |
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- | 0.0662 | 2.0 | 560 | 0.0840 | 0.9871 | 0.9873 | 0.9872 | 0.9872 |
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  ### Framework versions
 
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  base_model: xlm-roberta-base
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  tags:
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  - generated_from_trainer
 
 
 
 
 
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  model-index:
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  - name: intent_analysis
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  results: []
 
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  # intent_analysis
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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
 
 
 
 
 
 
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  ## Model description
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  - seed: 42
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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+ - num_epochs: 1
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | No log | 1.0 | 229 | 0.0529 | 0.9892 | 0.9892 | 0.9892 | 0.9892 |
 
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  ### Framework versions
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