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mariagrandury
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bluesky-spanish-classifier

Text Classification
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bert
Generated from Trainer
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  1. README.md +10 -9
  2. config.json +1 -1
  3. logs/events.out.tfevents.1740153701.a2d653e866f9.226.0 +3 -0
  4. model.safetensors +1 -1
  5. tokenizer_config.json +2 -1
  6. training_args.bin +2 -2
README.md CHANGED
@@ -1,4 +1,5 @@
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  ---
 
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  base_model: dccuchile/distilbert-base-spanish-uncased
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  tags:
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  - generated_from_trainer
@@ -14,8 +15,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [dccuchile/distilbert-base-spanish-uncased](https://huggingface.co/dccuchile/distilbert-base-spanish-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.1904
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- - Classification Report: {'ar': {'precision': 0.03571428571428571, 'recall': 0.00966183574879227, 'f1-score': 0.015209125475285171, 'support': 207.0}, 'cl': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 263.0}, 'co': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 171.0}, 'es': {'precision': 0.2221276595744681, 'recall': 0.786144578313253, 'f1-score': 0.34638354346383543, 'support': 332.0}, 'mx': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 203.0}, 'pe': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 161.0}, 'pr': {'precision': 0.010101010101010102, 'recall': 0.04, 'f1-score': 0.016129032258064516, 'support': 50.0}, 'uy': {'precision': 0.07142857142857142, 'recall': 0.05217391304347826, 'f1-score': 0.06030150753768844, 'support': 115.0}, 've': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 22.0}, 'accuracy': 0.1778215223097113, 'macro avg': {'precision': 0.03770794742425948, 'recall': 0.09866448078950261, 'f1-score': 0.04866924541498595, 'support': 1524.0}, 'weighted avg': {'precision': 0.05896232043367241, 'recall': 0.1778215223097113, 'f1-score': 0.08260416691805432, 'support': 1524.0}}
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  ## Model description
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@@ -38,21 +39,21 @@ The following hyperparameters were used during training:
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  - train_batch_size: 4
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  - eval_batch_size: 4
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  - seed: 42
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- - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 2
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  - training_steps: 2
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Classification Report |
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- |:-------------:|:------:|:----:|:---------------:|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
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- | 2.0868 | 0.0022 | 2 | 2.1904 | {'ar': {'precision': 0.03571428571428571, 'recall': 0.00966183574879227, 'f1-score': 0.015209125475285171, 'support': 207.0}, 'cl': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 263.0}, 'co': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 171.0}, 'es': {'precision': 0.2221276595744681, 'recall': 0.786144578313253, 'f1-score': 0.34638354346383543, 'support': 332.0}, 'mx': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 203.0}, 'pe': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 161.0}, 'pr': {'precision': 0.010101010101010102, 'recall': 0.04, 'f1-score': 0.016129032258064516, 'support': 50.0}, 'uy': {'precision': 0.07142857142857142, 'recall': 0.05217391304347826, 'f1-score': 0.06030150753768844, 'support': 115.0}, 've': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 22.0}, 'accuracy': 0.1778215223097113, 'macro avg': {'precision': 0.03770794742425948, 'recall': 0.09866448078950261, 'f1-score': 0.04866924541498595, 'support': 1524.0}, 'weighted avg': {'precision': 0.05896232043367241, 'recall': 0.1778215223097113, 'f1-score': 0.08260416691805432, 'support': 1524.0}} |
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  ### Framework versions
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- - Transformers 4.40.0
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- - Pytorch 2.6.0
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  - Datasets 3.3.2
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- - Tokenizers 0.19.1
 
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  ---
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+ library_name: transformers
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  base_model: dccuchile/distilbert-base-spanish-uncased
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  tags:
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  - generated_from_trainer
 
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  This model is a fine-tuned version of [dccuchile/distilbert-base-spanish-uncased](https://huggingface.co/dccuchile/distilbert-base-spanish-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.1812
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+ - Classification Report: {'ar': {'precision': 0.10526315789473684, 'recall': 0.08695652173913043, 'f1-score': 0.09523809523809523, 'support': 207.0}, 'cl': {'precision': 0.17346938775510204, 'recall': 0.19391634980988592, 'f1-score': 0.18312387791741472, 'support': 263.0}, 'co': {'precision': 0.06451612903225806, 'recall': 0.011695906432748537, 'f1-score': 0.019801980198019802, 'support': 171.0}, 'es': {'precision': 0.24783362218370883, 'recall': 0.4307228915662651, 'f1-score': 0.3146314631463146, 'support': 332.0}, 'mx': {'precision': 0.15086206896551724, 'recall': 0.1724137931034483, 'f1-score': 0.16091954022988506, 'support': 203.0}, 'pe': {'precision': 0.061946902654867256, 'recall': 0.043478260869565216, 'f1-score': 0.051094890510948905, 'support': 161.0}, 'pr': {'precision': 0.5, 'recall': 0.02, 'f1-score': 0.038461538461538464, 'support': 50.0}, 'uy': {'precision': 0.3181818181818182, 'recall': 0.06086956521739131, 'f1-score': 0.10218978102189781, 'support': 115.0}, 've': {'precision': 0.012195121951219513, 'recall': 0.045454545454545456, 'f1-score': 0.019230769230769232, 'support': 22.0}, 'accuracy': 0.17388451443569553, 'macro avg': {'precision': 0.18158535651324753, 'recall': 0.11838975935477558, 'f1-score': 0.10941021510609822, 'support': 1524.0}, 'weighted avg': {'precision': 0.1726919923848946, 'recall': 0.17388451443569553, 'f1-score': 0.151384890214964, 'support': 1524.0}}
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  ## Model description
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  - train_batch_size: 4
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  - eval_batch_size: 4
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  - seed: 42
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+ - optimizer: Use OptimizerNames.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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  - lr_scheduler_warmup_steps: 2
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  - training_steps: 2
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Classification Report |
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+ |:-------------:|:------:|:----:|:---------------:|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
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+ | 2.1638 | 0.0022 | 2 | 2.1812 | {'ar': {'precision': 0.10526315789473684, 'recall': 0.08695652173913043, 'f1-score': 0.09523809523809523, 'support': 207.0}, 'cl': {'precision': 0.17346938775510204, 'recall': 0.19391634980988592, 'f1-score': 0.18312387791741472, 'support': 263.0}, 'co': {'precision': 0.06451612903225806, 'recall': 0.011695906432748537, 'f1-score': 0.019801980198019802, 'support': 171.0}, 'es': {'precision': 0.24783362218370883, 'recall': 0.4307228915662651, 'f1-score': 0.3146314631463146, 'support': 332.0}, 'mx': {'precision': 0.15086206896551724, 'recall': 0.1724137931034483, 'f1-score': 0.16091954022988506, 'support': 203.0}, 'pe': {'precision': 0.061946902654867256, 'recall': 0.043478260869565216, 'f1-score': 0.051094890510948905, 'support': 161.0}, 'pr': {'precision': 0.5, 'recall': 0.02, 'f1-score': 0.038461538461538464, 'support': 50.0}, 'uy': {'precision': 0.3181818181818182, 'recall': 0.06086956521739131, 'f1-score': 0.10218978102189781, 'support': 115.0}, 've': {'precision': 0.012195121951219513, 'recall': 0.045454545454545456, 'f1-score': 0.019230769230769232, 'support': 22.0}, 'accuracy': 0.17388451443569553, 'macro avg': {'precision': 0.18158535651324753, 'recall': 0.11838975935477558, 'f1-score': 0.10941021510609822, 'support': 1524.0}, 'weighted avg': {'precision': 0.1726919923848946, 'recall': 0.17388451443569553, 'f1-score': 0.151384890214964, 'support': 1524.0}} |
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  ### Framework versions
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+ - Transformers 4.48.3
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+ - Pytorch 2.5.1+cu124
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  - Datasets 3.3.2
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+ - Tokenizers 0.21.0
config.json CHANGED
@@ -42,6 +42,6 @@
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  }
 
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  "torch_dtype": "float32",
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  "vocab_size": 31002
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