Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: bert-base-cased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: mi-clase-see2025ent
+  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. -->
+
+# mi-clase-see2025ent
+
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.3472
+- Accuracy: 0.53
+
+## 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: 5e-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
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.3711        | 1.0   | 38   | 1.3176          | 0.47     |
+| 0.8469        | 2.0   | 76   | 1.1336          | 0.54     |
+| 0.5777        | 3.0   | 114  | 1.1880          | 0.54     |
+| 0.5556        | 4.0   | 152  | 1.2859          | 0.52     |
+| 0.1975        | 5.0   | 190  | 1.3610          | 0.55     |
+| 0.2516        | 6.0   | 228  | 1.9845          | 0.5      |
+| 0.0281        | 7.0   | 266  | 2.3607          | 0.47     |
+| 0.0062        | 8.0   | 304  | 2.3559          | 0.51     |
+| 0.0043        | 9.0   | 342  | 2.3073          | 0.54     |
+| 0.0041        | 10.0  | 380  | 2.3472          | 0.53     |
+
+
+### Framework versions
+
+- Transformers 4.53.1
+- Pytorch 2.7.1+cu118
+- Datasets 3.6.0
+- Tokenizers 0.21.2

model.safetensors

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