End of training

README.md

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+---
+base_model: dccuchile/bert-base-spanish-wwm-cased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- recall
+model-index:
+- name: ClasificadorV2
+  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. -->
+
+# ClasificadorV2
+
+This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-cased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1411
+- Accuracy: 0.5708
+- Off By One Accuracy: 0.9434
+- F1: 0.5724
+- Recall: 0.5708
+
+## 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: 50
+- eval_batch_size: 50
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Off By One Accuracy | F1     | Recall |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:-------------------:|:------:|:------:|
+| 1.2177        | 0.3333 | 500  | 1.0309          | 0.5426   | 0.93                | 0.5414 | 0.5426 |
+| 1.011         | 0.6667 | 1000 | 0.9836          | 0.565    | 0.9336              | 0.5485 | 0.565  |
+| 0.9833        | 1.0    | 1500 | 0.9664          | 0.5752   | 0.9448              | 0.5704 | 0.5752 |
+| 0.9004        | 1.3333 | 2000 | 0.9566          | 0.5728   | 0.9476              | 0.5743 | 0.5728 |
+| 0.8974        | 1.6667 | 2500 | 0.9583          | 0.5782   | 0.9472              | 0.5784 | 0.5782 |
+| 0.8912        | 2.0    | 3000 | 0.9480          | 0.5816   | 0.9498              | 0.5768 | 0.5816 |
+| 0.7935        | 2.3333 | 3500 | 0.9768          | 0.582    | 0.9472              | 0.5800 | 0.582  |
+| 0.7898        | 2.6667 | 4000 | 0.9831          | 0.5716   | 0.9426              | 0.5715 | 0.5716 |
+| 0.7801        | 3.0    | 4500 | 0.9969          | 0.5736   | 0.9514              | 0.5759 | 0.5736 |
+| 0.6714        | 3.3333 | 5000 | 1.0782          | 0.5826   | 0.9392              | 0.5795 | 0.5826 |
+| 0.6783        | 3.6667 | 5500 | 1.0672          | 0.5724   | 0.9456              | 0.5752 | 0.5724 |
+| 0.6764        | 4.0    | 6000 | 1.0762          | 0.567    | 0.9458              | 0.5708 | 0.567  |
+| 0.5986        | 4.3333 | 6500 | 1.1349          | 0.5698   | 0.9412              | 0.5684 | 0.5698 |
+| 0.5887        | 4.6667 | 7000 | 1.1335          | 0.5706   | 0.9398              | 0.5716 | 0.5706 |
+| 0.5798        | 5.0    | 7500 | 1.1411          | 0.5708   | 0.9434              | 0.5724 | 0.5708 |
+
+
+### Framework versions
+
+- Transformers 4.40.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "dccuchile/bert-base-spanish-wwm-cased",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.5,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.5,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3",
+    "4": "LABEL_4"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2,
+    "LABEL_3": 3,
+    "LABEL_4": 4
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "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",
+  "torch_dtype": "float32",
+  "transformers_version": "4.40.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 31002
+}

model.safetensors

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training_args.bin

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