Update README.md

README.md

@@ -1,69 +1,70 @@
----
-base_model: daveni/twitter-xlm-roberta-emotion-es
-tags:
-- generated_from_trainer
-metrics:
-- accuracy
-- f1
-- precision
-- recall
-model-index:
-- name: base
-  results: []
----
-
-<!-- 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. -->
-
-# base
-
-This model is a fine-tuned version of [daveni/twitter-xlm-roberta-emotion-es](https://huggingface.co/daveni/twitter-xlm-roberta-emotion-es) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.4881
-- Accuracy: 0.8504
-- F1: 0.8119
-- Precision: 0.8454
-- Recall: 0.7810
-
-## 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: 32
-- 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 |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
-| 0.667         | 1.0   | 32   | 0.5528          | 0.7283   | 0.6057 | 0.7571    | 0.5048 |
-| 0.5241        | 2.0   | 64   | 0.4843          | 0.7874   | 0.7065 | 0.8228    | 0.6190 |
-| 0.3046        | 3.0   | 96   | 0.4785          | 0.8031   | 0.7423 | 0.8090    | 0.6857 |
-| 0.1631        | 4.0   | 128  | 0.4776          | 0.8228   | 0.7644 | 0.8488    | 0.6952 |
-| 0.097         | 5.0   | 160  | 0.4881          | 0.8504   | 0.8119 | 0.8454    | 0.7810 |
-
-
-### Framework versions
-
-- Transformers 4.43.3
-- Pytorch 2.4.0
-- Datasets 2.20.0
-- Tokenizers 0.19.1
+---
+base_model: daveni/twitter-xlm-roberta-emotion-es
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: base
+  results: []
+pipeline_tag: text-classification
+---
+
+<!-- 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. -->
+
+# base
+
+This model is a fine-tuned version of [daveni/twitter-xlm-roberta-emotion-es](https://huggingface.co/daveni/twitter-xlm-roberta-emotion-es) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4881
+- Accuracy: 0.8504
+- F1: 0.8119
+- Precision: 0.8454
+- Recall: 0.7810
+
+## 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: 32
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.667         | 1.0   | 32   | 0.5528          | 0.7283   | 0.6057 | 0.7571    | 0.5048 |
+| 0.5241        | 2.0   | 64   | 0.4843          | 0.7874   | 0.7065 | 0.8228    | 0.6190 |
+| 0.3046        | 3.0   | 96   | 0.4785          | 0.8031   | 0.7423 | 0.8090    | 0.6857 |
+| 0.1631        | 4.0   | 128  | 0.4776          | 0.8228   | 0.7644 | 0.8488    | 0.6952 |
+| 0.097         | 5.0   | 160  | 0.4881          | 0.8504   | 0.8119 | 0.8454    | 0.7810 |
+
+
+### Framework versions
+
+- Transformers 4.43.3
+- Pytorch 2.4.0
+- Datasets 2.20.0
+- Tokenizers 0.19.1