update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- amazon_reviews_multi
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: selectra-small-finetuned-amazon-review
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: amazon_reviews_multi
+      type: amazon_reviews_multi
+      args: es
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.737
+    - name: F1
+      type: f1
+      value: 0.7437773019932409
+    - name: Precision
+      type: precision
+      value: 0.7524857881639091
+    - name: Recall
+      type: recall
+      value: 0.737
+---
+
+<!-- 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. -->
+
+# selectra-small-finetuned-amazon-review
+
+This model is a fine-tuned version of [Recognai/selectra_small](https://huggingface.co/Recognai/selectra_small) on the amazon_reviews_multi dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6279
+- Accuracy: 0.737
+- F1: 0.7438
+- Precision: 0.7525
+- Recall: 0.737
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| No log        | 0.5   | 500  | 0.7041          | 0.7178   | 0.6724 | 0.6715    | 0.7178 |
+| 0.7908        | 1.0   | 1000 | 0.6365          | 0.7356   | 0.7272 | 0.7211    | 0.7356 |
+| 0.7908        | 1.5   | 1500 | 0.6204          | 0.7376   | 0.7380 | 0.7387    | 0.7376 |
+| 0.6358        | 2.0   | 2000 | 0.6162          | 0.7386   | 0.7377 | 0.7380    | 0.7386 |
+| 0.6358        | 2.5   | 2500 | 0.6228          | 0.7274   | 0.7390 | 0.7576    | 0.7274 |
+| 0.5827        | 3.0   | 3000 | 0.6188          | 0.7378   | 0.7400 | 0.7425    | 0.7378 |
+| 0.5827        | 3.5   | 3500 | 0.6246          | 0.7374   | 0.7416 | 0.7467    | 0.7374 |
+| 0.5427        | 4.0   | 4000 | 0.6266          | 0.7446   | 0.7452 | 0.7465    | 0.7446 |
+| 0.5427        | 4.5   | 4500 | 0.6331          | 0.7392   | 0.7421 | 0.7456    | 0.7392 |
+| 0.5184        | 5.0   | 5000 | 0.6279          | 0.737    | 0.7438 | 0.7525    | 0.737  |
+
+
+### Framework versions
+
+- Transformers 4.15.0
+- Pytorch 1.10.0+cu111
+- Datasets 1.17.0
+- Tokenizers 0.10.3