adriansanz commited on
Commit
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clasificador_xml_5ep_v2

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README.md CHANGED
@@ -4,6 +4,11 @@ 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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  model-index:
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  - name: intent_analysis
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  results: []
@@ -15,6 +20,12 @@ 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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  ## Model description
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@@ -33,19 +44,22 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 5e-05
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- - train_batch_size: 16
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- - eval_batch_size: 16
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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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  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: []
 
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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: 0.0750
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+ - Accuracy: 0.9781
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+ - Precision: 0.9782
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+ - Recall: 0.9781
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+ - F1: 0.9781
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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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: cosine
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 3
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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 | 114 | 0.1457 | 0.9459 | 0.9498 | 0.9459 | 0.9456 |
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+ | No log | 2.0 | 228 | 0.0754 | 0.9774 | 0.9777 | 0.9774 | 0.9775 |
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+ | No log | 3.0 | 342 | 0.0750 | 0.9781 | 0.9782 | 0.9781 | 0.9781 |
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  ### Framework versions
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