update model card README.md

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- dataset
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: dccuchile-distilbert-base-spanish-uncased-finetuned-with-spanish-tweets-clf-cleaned-ds
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: dataset
+      type: dataset
+      config: 60-20-20
+      split: dev
+      args: 60-20-20
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.650310988251555
+    - name: F1
+      type: f1
+      value: 0.6518765643027159
+    - name: Precision
+      type: precision
+      value: 0.6625453481119005
+    - name: Recall
+      type: recall
+      value: 0.6498098682990169
+---
+
+<!-- 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. -->
+
+# dccuchile-distilbert-base-spanish-uncased-finetuned-with-spanish-tweets-clf-cleaned-ds
+
+This model is a fine-tuned version of [dccuchile/distilbert-base-spanish-uncased](https://huggingface.co/dccuchile/distilbert-base-spanish-uncased) on the dataset dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.6605
+- Accuracy: 0.6503
+- F1: 0.6519
+- Precision: 0.6625
+- Recall: 0.6498
+
+## 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: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.8558        | 1.0   | 543  | 0.7705          | 0.6628   | 0.6408 | 0.6585    | 0.6404 |
+| 0.5485        | 2.0   | 1086 | 0.8657          | 0.6593   | 0.6436 | 0.6578    | 0.6388 |
+| 0.3071        | 3.0   | 1629 | 1.3021          | 0.6586   | 0.6556 | 0.6551    | 0.6581 |
+| 0.1581        | 4.0   | 2172 | 1.6605          | 0.6503   | 0.6519 | 0.6625    | 0.6498 |
+
+
+### Framework versions
+
+- Transformers 4.26.0
+- Pytorch 1.13.1
+- Datasets 2.8.0
+- Tokenizers 0.13.2