update model card README.md

README.md

@@ -1,3 +1,92 @@
 ---
 license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- dataset
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: distilbert-base-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: 0.5556323427781618
+    - name: F1
+      type: f1
+      value: 0.5577964748279268
+    - name: Precision
+      type: precision
+      value: 0.5682169161320979
+    - name: Recall
+      type: recall
+      value: 0.5539741666889855
 ---
+
+<!-- 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. -->
+
+# distilbert-base-uncased-finetuned-with-spanish-tweets-clf-cleaned-ds
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the dataset dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1229
+- Accuracy: 0.5556
+- F1: 0.5578
+- Precision: 0.5682
+- Recall: 0.5540
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 1.0683        | 1.0   | 543  | 1.0019          | 0.4997   | 0.4041 | 0.4724    | 0.4488 |
+| 0.9372        | 2.0   | 1086 | 0.9395          | 0.5425   | 0.5143 | 0.5480    | 0.5123 |
+| 0.7283        | 3.0   | 1629 | 0.9674          | 0.5632   | 0.5615 | 0.5658    | 0.5587 |
+| 0.5127        | 4.0   | 2172 | 1.1229          | 0.5556   | 0.5578 | 0.5682    | 0.5540 |
+
+
+### Framework versions
+
+- Transformers 4.26.0
+- Pytorch 1.13.1
+- Datasets 2.8.0
+- Tokenizers 0.13.2