End of training

README.md

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+---
+base_model: dccuchile/bert-base-spanish-wwm-uncased
+tags:
+- generated_from_trainer
+datasets:
+- muchocine
+metrics:
+- accuracy
+model-index:
+- name: bert-base-uncased-es-sentiment-analysis
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: muchocine
+      type: muchocine
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.792258064516129
+---
+
+<!-- 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-uncased-es-sentiment-analysis
+
+This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-uncased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-uncased) on the muchocine dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9713
+- Accuracy: 0.7923
+
+## 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: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.541         | 1.0   | 49   | 0.4618          | 0.7781   |
+| 0.3157        | 2.0   | 98   | 0.4989          | 0.7742   |
+| 0.1294        | 3.0   | 147  | 0.6931          | 0.8      |
+| 0.0541        | 4.0   | 196  | 0.8284          | 0.7935   |
+| 0.0254        | 5.0   | 245  | 0.9713          | 0.7923   |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1