End of training

README.md

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+---
+base_model: dccuchile/distilbert-base-spanish-uncased
+tags:
+- generated_from_trainer
+model-index:
+- name: bluesky-spanish-classifier
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# bluesky-spanish-classifier
+
+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.
+It achieves the following results on the evaluation set:
+- Loss: 2.1904
+- 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}}
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 2
+- training_steps: 2
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Classification Report                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 |
+|:-------------:|:------:|:----:|:---------------:|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
+| 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}} |
+
+
+### Framework versions
+
+- Transformers 4.40.0
+- Pytorch 2.6.0
+- Datasets 3.3.2
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "dccuchile/distilbert-base-spanish-uncased",
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForSequenceClassification"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "hidden_dim": 3072,
+  "id2label": {
+    "0": "ar",
+    "1": "cl",
+    "2": "co",
+    "3": "es",
+    "4": "mx",
+    "5": "pe",
+    "6": "pr",
+    "7": "uy",
+    "8": "ve"
+  },
+  "initializer_range": 0.02,
+  "label2id": {
+    "ar": 0,
+    "cl": 1,
+    "co": 2,
+    "es": 3,
+    "mx": 4,
+    "pe": 5,
+    "pr": 6,
+    "uy": 7,
+    "ve": 8
+  },
+  "max_position_embeddings": 512,
+  "model_type": "distilbert",
+  "n_heads": 12,
+  "n_layers": 6,
+  "pad_token_id": 0,
+  "problem_type": "single_label_classification",
+  "qa_dropout": 0.1,
+  "seq_classif_dropout": 0.2,
+  "sinusoidal_pos_embds": true,
+  "tie_weights_": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.40.0",
+  "vocab_size": 31002
+}

model.safetensors

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special_tokens_map.json

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+{
+  "cls_token": {
+    "content": "[CLS]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+  "mask_token": {
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+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+    "lstrip": false,
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+    "rstrip": false,
+    "single_word": false
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+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "lstrip": false,
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+      "special": true
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+      "normalized": false,
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+      "single_word": false,
+      "special": true
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+      "lstrip": false,
+      "normalized": false,
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+      "single_word": false,
+      "special": true
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+  },
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": false,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "DistilBertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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