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: electra-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: 0.4948
+    - name: F1
+      type: f1
+      value: 0.49332463542809535
+    - name: Precision
+      type: precision
+      value: 0.4921725374649701
+    - name: Recall
+      type: recall
+      value: 0.4948
+---
+
+<!-- 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. -->
+
+# electra-small-finetuned-amazon-review
+
+This model is a fine-tuned version of [google/electra-small-discriminator](https://huggingface.co/google/electra-small-discriminator) on the amazon_reviews_multi dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1647
+- Accuracy: 0.4948
+- F1: 0.4933
+- Precision: 0.4922
+- Recall: 0.4948
+
+## 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: 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
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 1.4061        | 1.0   | 1000 | 1.2279          | 0.4496   | 0.4230 | 0.4359    | 0.4496 |
+| 1.1941        | 2.0   | 2000 | 1.1783          | 0.4782   | 0.4586 | 0.4567    | 0.4782 |
+| 1.0997        | 3.0   | 3000 | 1.1648          | 0.4966   | 0.4785 | 0.4805    | 0.4966 |
+| 1.0265        | 4.0   | 4000 | 1.1507          | 0.4996   | 0.4932 | 0.4920    | 0.4996 |
+| 0.9736        | 5.0   | 5000 | 1.1647          | 0.4948   | 0.4933 | 0.4922    | 0.4948 |
+
+
+### Framework versions
+
+- Transformers 4.15.0
+- Pytorch 1.10.0+cu111
+- Datasets 1.17.0
+- Tokenizers 0.10.3