End of training

README.md

@@ -1,8 +1,10 @@
 ---
 library_name: transformers
-base_model: dccuchile/distilbert-base-spanish-uncased
+base_model: dccuchile/bert-base-spanish-wwm-uncased
 tags:
 - generated_from_trainer
+metrics:
+- f1
 model-index:
 - name: bluesky-spanish-classifier
   results: []
@@ -13,10 +15,11 @@ 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.
+This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-uncased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-uncased) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 2.2149
-- Classification Report: {'ar': {'precision': 0.125, 'recall': 0.014492753623188406, 'f1-score': 0.025974025974025976, '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': 0.6666666666666666, 'recall': 0.006024096385542169, 'f1-score': 0.011940298507462687, 'support': 332.0}, 'mx': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 203.0}, 'pe': {'precision': 0.03333333333333333, 'recall': 0.006211180124223602, 'f1-score': 0.010471204188481676, 'support': 161.0}, 'pr': {'precision': 0.09401709401709402, 'recall': 0.22, 'f1-score': 0.1317365269461078, 'support': 50.0}, 'uy': {'precision': 0.07073715562174236, 'recall': 0.8260869565217391, 'f1-score': 0.13031550068587106, 'support': 115.0}, 've': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 22.0}, 'accuracy': 0.07349081364829396, 'macro avg': {'precision': 0.10997269440431515, 'recall': 0.1192016651838548, 'f1-score': 0.03449306181132769, 'support': 1524.0}, 'weighted avg': {'precision': 0.17415395511637471, 'recall': 0.07349081364829396, 'f1-score': 0.021390928662484977, 'support': 1524.0}}
+- Loss: 2.3731
+- Classification Report: {'ar': {'precision': 0.4898785425101215, 'recall': 0.32180851063829785, 'f1-score': 0.3884430176565008, 'support': 376.0}, 'cl': {'precision': 0.3626666666666667, 'recall': 0.4722222222222222, 'f1-score': 0.41025641025641024, 'support': 576.0}, 'co': {'precision': 0.34656084656084657, 'recall': 0.3808139534883721, 'f1-score': 0.3628808864265928, 'support': 344.0}, 'es': {'precision': 0.4630738522954092, 'recall': 0.427255985267035, 'f1-score': 0.4444444444444444, 'support': 543.0}, 'mx': {'precision': 0.43380855397148677, 'recall': 0.43917525773195876, 'f1-score': 0.4364754098360656, 'support': 485.0}, 'pe': {'precision': 0.3769968051118211, 'recall': 0.3390804597701149, 'f1-score': 0.35703479576399394, 'support': 348.0}, 'pr': {'precision': 0.5736434108527132, 'recall': 0.7326732673267327, 'f1-score': 0.6434782608695652, 'support': 101.0}, 'uy': {'precision': 0.35096153846153844, 'recall': 0.3201754385964912, 'f1-score': 0.3348623853211009, 'support': 228.0}, 've': {'precision': 0.16666666666666666, 'recall': 0.045454545454545456, 'f1-score': 0.07142857142857142, 'support': 22.0}, 'accuracy': 0.4085345683096262, 'macro avg': {'precision': 0.39602854256636333, 'recall': 0.38651773783286336, 'f1-score': 0.3832560202225828, 'support': 3023.0}, 'weighted avg': {'precision': 0.4124949665181113, 'recall': 0.4085345683096262, 'f1-score': 0.40601279016852304, 'support': 3023.0}}
+- F1: 0.3833
 
 ## Model description
 
@@ -35,20 +38,24 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 2e-05
-- train_batch_size: 4
-- eval_batch_size: 4
+- learning_rate: 2.8600231011639855e-05
+- train_batch_size: 8
+- eval_batch_size: 8
 - seed: 42
 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 2
-- training_steps: 2
+- lr_scheduler_warmup_ratio: 0.11531859504380029
+- num_epochs: 5
 
 ### Training results
 
-| Training Loss | Epoch  | Step | Validation Loss | Classification Report                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        |
-|:-------------:|:------:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
-| 2.2248        | 0.0022 | 2    | 2.2149          | {'ar': {'precision': 0.125, 'recall': 0.014492753623188406, 'f1-score': 0.025974025974025976, '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': 0.6666666666666666, 'recall': 0.006024096385542169, 'f1-score': 0.011940298507462687, 'support': 332.0}, 'mx': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 203.0}, 'pe': {'precision': 0.03333333333333333, 'recall': 0.006211180124223602, 'f1-score': 0.010471204188481676, 'support': 161.0}, 'pr': {'precision': 0.09401709401709402, 'recall': 0.22, 'f1-score': 0.1317365269461078, 'support': 50.0}, 'uy': {'precision': 0.07073715562174236, 'recall': 0.8260869565217391, 'f1-score': 0.13031550068587106, 'support': 115.0}, 've': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 22.0}, 'accuracy': 0.07349081364829396, 'macro avg': {'precision': 0.10997269440431515, 'recall': 0.1192016651838548, 'f1-score': 0.03449306181132769, 'support': 1524.0}, 'weighted avg': {'precision': 0.17415395511637471, 'recall': 0.07349081364829396, 'f1-score': 0.021390928662484977, 'support': 1524.0}} |
+| Training Loss | Epoch | Step | Validation Loss | Classification Report                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:------:|
+| 1.7603        | 1.0   | 882  | 1.7406          | {'ar': {'precision': 0.35516372795969775, 'recall': 0.375, 'f1-score': 0.3648124191461837, 'support': 376.0}, 'cl': {'precision': 0.3016759776536313, 'recall': 0.28125, 'f1-score': 0.29110512129380056, 'support': 576.0}, 'co': {'precision': 0.3670886075949367, 'recall': 0.25290697674418605, 'f1-score': 0.29948364888123924, 'support': 344.0}, 'es': {'precision': 0.3584905660377358, 'recall': 0.4548802946593002, 'f1-score': 0.400974025974026, 'support': 543.0}, 'mx': {'precision': 0.32465753424657534, 'recall': 0.488659793814433, 'f1-score': 0.39012345679012345, 'support': 485.0}, 'pe': {'precision': 0.3958333333333333, 'recall': 0.27298850574712646, 'f1-score': 0.3231292517006803, 'support': 348.0}, 'pr': {'precision': 0.5631067961165048, 'recall': 0.5742574257425742, 'f1-score': 0.5686274509803921, 'support': 101.0}, 'uy': {'precision': 0.4666666666666667, 'recall': 0.18421052631578946, 'f1-score': 0.2641509433962264, 'support': 228.0}, 've': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 22.0}, 'accuracy': 0.3536222295732716, 'macro avg': {'precision': 0.34807591217878686, 'recall': 0.3204615025581566, 'f1-score': 0.32248959090696355, 'support': 3023.0}, 'weighted avg': {'precision': 0.35948675942105285, 'recall': 0.3536222295732716, 'f1-score': 0.3456546260541325, 'support': 3023.0}}                                                                          | 0.3225 |
+| 1.4223        | 2.0   | 1764 | 1.6758          | {'ar': {'precision': 0.4349315068493151, 'recall': 0.3377659574468085, 'f1-score': 0.38023952095808383, 'support': 376.0}, 'cl': {'precision': 0.336996336996337, 'recall': 0.3194444444444444, 'f1-score': 0.32798573975044565, 'support': 576.0}, 'co': {'precision': 0.36333333333333334, 'recall': 0.3168604651162791, 'f1-score': 0.3385093167701863, 'support': 344.0}, 'es': {'precision': 0.38980716253443526, 'recall': 0.5211786372007366, 'f1-score': 0.44602048857368004, 'support': 543.0}, 'mx': {'precision': 0.35246995994659547, 'recall': 0.5443298969072164, 'f1-score': 0.42787682333873583, 'support': 485.0}, 'pe': {'precision': 0.44308943089430897, 'recall': 0.3132183908045977, 'f1-score': 0.367003367003367, 'support': 348.0}, 'pr': {'precision': 0.759493670886076, 'recall': 0.594059405940594, 'f1-score': 0.6666666666666666, 'support': 101.0}, 'uy': {'precision': 0.5542168674698795, 'recall': 0.20175438596491227, 'f1-score': 0.2958199356913183, 'support': 228.0}, 've': {'precision': 1.0, 'recall': 0.09090909090909091, 'f1-score': 0.16666666666666666, 'support': 22.0}, 'accuracy': 0.3916639100231558, 'macro avg': {'precision': 0.5149264743233645, 'recall': 0.35994674163718665, 'f1-score': 0.3796431694910167, 'support': 3023.0}, 'weighted avg': {'precision': 0.4116802685001794, 'recall': 0.3916639100231558, 'f1-score': 0.3851176158170783, 'support': 3023.0}}                     | 0.3796 |
+| 0.9068        | 3.0   | 2646 | 1.9523          | {'ar': {'precision': 0.39574468085106385, 'recall': 0.4946808510638298, 'f1-score': 0.4397163120567376, 'support': 376.0}, 'cl': {'precision': 0.35144927536231885, 'recall': 0.3368055555555556, 'f1-score': 0.34397163120567376, 'support': 576.0}, 'co': {'precision': 0.31555555555555553, 'recall': 0.4127906976744186, 'f1-score': 0.35768261964735515, 'support': 344.0}, 'es': {'precision': 0.47113163972286376, 'recall': 0.3756906077348066, 'f1-score': 0.4180327868852459, 'support': 543.0}, 'mx': {'precision': 0.43680709534368073, 'recall': 0.4061855670103093, 'f1-score': 0.42094017094017094, 'support': 485.0}, 'pe': {'precision': 0.38661710037174724, 'recall': 0.2988505747126437, 'f1-score': 0.3371150729335494, 'support': 348.0}, 'pr': {'precision': 0.64, 'recall': 0.6336633663366337, 'f1-score': 0.6368159203980099, 'support': 101.0}, 'uy': {'precision': 0.30662020905923343, 'recall': 0.38596491228070173, 'f1-score': 0.341747572815534, 'support': 228.0}, 've': {'precision': 0.18181818181818182, 'recall': 0.09090909090909091, 'f1-score': 0.12121212121212122, 'support': 22.0}, 'accuracy': 0.3906715183592458, 'macro avg': {'precision': 0.3873048597871828, 'recall': 0.3817268025864433, 'f1-score': 0.37969268978826637, 'support': 3023.0}, 'weighted avg': {'precision': 0.3971399185993649, 'recall': 0.3906715183592458, 'f1-score': 0.3902981034934984, 'support': 3023.0}}              | 0.3797 |
+| 0.4818        | 4.0   | 3528 | 2.3731          | {'ar': {'precision': 0.4898785425101215, 'recall': 0.32180851063829785, 'f1-score': 0.3884430176565008, 'support': 376.0}, 'cl': {'precision': 0.3626666666666667, 'recall': 0.4722222222222222, 'f1-score': 0.41025641025641024, 'support': 576.0}, 'co': {'precision': 0.34656084656084657, 'recall': 0.3808139534883721, 'f1-score': 0.3628808864265928, 'support': 344.0}, 'es': {'precision': 0.4630738522954092, 'recall': 0.427255985267035, 'f1-score': 0.4444444444444444, 'support': 543.0}, 'mx': {'precision': 0.43380855397148677, 'recall': 0.43917525773195876, 'f1-score': 0.4364754098360656, 'support': 485.0}, 'pe': {'precision': 0.3769968051118211, 'recall': 0.3390804597701149, 'f1-score': 0.35703479576399394, 'support': 348.0}, 'pr': {'precision': 0.5736434108527132, 'recall': 0.7326732673267327, 'f1-score': 0.6434782608695652, 'support': 101.0}, 'uy': {'precision': 0.35096153846153844, 'recall': 0.3201754385964912, 'f1-score': 0.3348623853211009, 'support': 228.0}, 've': {'precision': 0.16666666666666666, 'recall': 0.045454545454545456, 'f1-score': 0.07142857142857142, 'support': 22.0}, 'accuracy': 0.4085345683096262, 'macro avg': {'precision': 0.39602854256636333, 'recall': 0.38651773783286336, 'f1-score': 0.3832560202225828, 'support': 3023.0}, 'weighted avg': {'precision': 0.4124949665181113, 'recall': 0.4085345683096262, 'f1-score': 0.40601279016852304, 'support': 3023.0}} | 0.3833 |
+| 0.2357        | 5.0   | 4410 | 2.7721          | {'ar': {'precision': 0.42168674698795183, 'recall': 0.3723404255319149, 'f1-score': 0.3954802259887006, 'support': 376.0}, 'cl': {'precision': 0.38753799392097266, 'recall': 0.4427083333333333, 'f1-score': 0.413290113452188, 'support': 576.0}, 'co': {'precision': 0.35051546391752575, 'recall': 0.3953488372093023, 'f1-score': 0.37158469945355194, 'support': 344.0}, 'es': {'precision': 0.4642857142857143, 'recall': 0.40699815837937386, 'f1-score': 0.4337585868498528, 'support': 543.0}, 'mx': {'precision': 0.43089430894308944, 'recall': 0.43711340206185567, 'f1-score': 0.43398157625383826, 'support': 485.0}, 'pe': {'precision': 0.3407960199004975, 'recall': 0.3936781609195402, 'f1-score': 0.36533333333333334, 'support': 348.0}, 'pr': {'precision': 0.6601941747572816, 'recall': 0.6732673267326733, 'f1-score': 0.6666666666666666, 'support': 101.0}, 'uy': {'precision': 0.40853658536585363, 'recall': 0.29385964912280704, 'f1-score': 0.34183673469387754, 'support': 228.0}, 've': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 22.0}, 'accuracy': 0.40886536553092956, 'macro avg': {'precision': 0.3849385564532096, 'recall': 0.3794793659212001, 'f1-score': 0.38021465963244544, 'support': 3023.0}, 'weighted avg': {'precision': 0.41080624270175103, 'recall': 0.40886536553092956, 'f1-score': 0.4078732692419294, 'support': 3023.0}}                                            | 0.3802 |
 
 
 ### Framework versions

config.json

@@ -1,13 +1,14 @@
 {
-  "_name_or_path": "dccuchile/distilbert-base-spanish-uncased",
-  "activation": "gelu",
+  "_name_or_path": "dccuchile/bert-base-spanish-wwm-uncased",
   "architectures": [
-    "DistilBertForSequenceClassification"
+    "BertForSequenceClassification"
   ],
-  "attention_dropout": 0.1,
-  "dim": 768,
-  "dropout": 0.1,
-  "hidden_dim": 3072,
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
   "id2label": {
     "0": "ar",
     "1": "cl",
@@ -20,6 +21,7 @@
     "8": "ve"
   },
   "initializer_range": 0.02,
+  "intermediate_size": 3072,
   "label2id": {
     "ar": 0,
     "cl": 1,
@@ -31,17 +33,18 @@
     "uy": 7,
     "ve": 8
   },
+  "layer_norm_eps": 1e-12,
   "max_position_embeddings": 512,
-  "model_type": "distilbert",
-  "n_heads": 12,
-  "n_layers": 6,
-  "pad_token_id": 0,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
   "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": "4.48.3",
+  "type_vocab_size": 2,
+  "use_cache": true,
   "vocab_size": 31002
 }

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model.safetensors

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model_stats.json

@@ -1,177 +1,96 @@
 {
   "dataset": {
-    "splits": {
+    "train_size": 3553,
+    "test_size": 1524,
+    "country_distribution": {
       "train": {
-        "num_examples": 3553,
-        "features": [
-          "author",
-          "country",
-          "post_text",
-          "created_at",
-          "likes",
-          "quotes",
-          "replies",
-          "reposts",
-          "post_id",
-          "lang",
-          "tags",
-          "image_links",
-          "profile_info",
-          "processed_text",
-          "__index_level_0__"
-        ],
-        "first_example": {
-          "author": "apalet.bsky.social",
-          "country": "cl",
-          "post_text": "Me lloran los ojos sin pedir permiso ni razón.",
-          "created_at": "2024-12-31T01:15:04.751Z",
-          "likes": 8,
-          "quotes": 0,
-          "replies": 1,
-          "reposts": 0,
-          "post_id": "at://did:plc:y4bvfcu7wrx7jlyjg6qglqzl/app.bsky.feed.post/3lekuofg3xk2v",
-          "lang": "es",
-          "tags": "",
-          "image_links": "",
-          "profile_info": {
-            "description": "Leo y olvido \nwww.laurel.cl\nhttps://revistadossier.udp.cl",
-            "display_name": "Andrea Palet",
-            "feed_uri": null,
-            "followers_count": 1355,
-            "follows_count": 304,
-            "indexed_at": "2024-11-30T20:22:38.048Z",
-            "posts_count": 515
-          },
-          "processed_text": "lloran ojos pedir permiso razón",
-          "__index_level_0__": 4653
+        "ar": {
+          "count": 483,
+          "percentage": 13.594145792288206
+        },
+        "cl": {
+          "count": 614,
+          "percentage": 17.28117084154236
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+        "co": {
+          "count": 399,
+          "percentage": 11.229946524064172
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+        "es": {
+          "count": 774,
+          "percentage": 21.784407542921475
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+        "mx": {
+          "count": 473,
+          "percentage": 13.312693498452013
         },
-        "country_distribution": {
-          "ar": {
-            "count": 483,
-            "percentage": 13.594145792288206
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-          "cl": {
-            "count": 614,
-            "percentage": 17.28117084154236
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-          "ve": {
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       },
       "test": {
-        "num_examples": 1524,
-        "features": [
-          "author",
-          "country",
-          "post_text",
-          "created_at",
-          "likes",
-          "quotes",
-          "replies",
-          "reposts",
-          "post_id",
-          "lang",
-          "tags",
-          "image_links",
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