Model save

README.md

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+---
+base_model: dccuchile/bert-base-spanish-wwm-cased
+tags:
+- generated_from_trainer
+metrics:
+- f1
+- recall
+model-index:
+- name: bert-base-spanish-wwm-cased_K2
+  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. -->
+
+# bert-base-spanish-wwm-cased_K2
+
+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: 0.1222
+- F1 Macro: 0.9798
+- F1: 0.9852
+- F1 Neg: 0.9744
+- Acc: 0.9812
+- Prec: 0.9862
+- Recall: 0.9843
+- Mcc: 0.9596
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1     | F1 Neg | Acc    | Prec   | Recall | Mcc    |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|:------:|:------:|
+| No log        | 1.0   | 400  | 0.0777          | 0.9784   | 0.9843 | 0.9725 | 0.98   | 0.9824 | 0.9862 | 0.9568 |
+| 0.2063        | 2.0   | 800  | 0.1065          | 0.9784   | 0.9843 | 0.9726 | 0.98   | 0.9843 | 0.9843 | 0.9569 |
+| 0.0791        | 3.0   | 1200 | 0.1388          | 0.9743   | 0.9814 | 0.9672 | 0.9762 | 0.9766 | 0.9862 | 0.9487 |
+| 0.0298        | 4.0   | 1600 | 0.1222          | 0.9798   | 0.9852 | 0.9744 | 0.9812 | 0.9862 | 0.9843 | 0.9596 |
+| 0.0052        | 5.0   | 2000 | 0.1608          | 0.9732   | 0.9801 | 0.9663 | 0.975  | 0.9900 | 0.9705 | 0.9468 |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

model.safetensors

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