End of training

README.md

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+---
+base_model: daveni/twitter-xlm-roberta-emotion-es
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: xml-roberta-HU-Com
+  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. -->
+
+# xml-roberta-HU-Com
+
+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: 1.3693
+- Accuracy: 0.7911
+- F1: 0.7440
+- Precision: 0.7415
+- Recall: 0.7466
+
+## 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: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.6717        | 1.0   | 90   | 0.5918          | 0.6852   | 0.5272 | 0.6774    | 0.4315 |
+| 0.453         | 2.0   | 180  | 0.5358          | 0.7465   | 0.6403 | 0.7570    | 0.5548 |
+| 0.2631        | 3.0   | 270  | 0.7088          | 0.7744   | 0.7273 | 0.7152    | 0.7397 |
+| 0.1936        | 4.0   | 360  | 0.7078          | 0.7939   | 0.7566 | 0.7278    | 0.7877 |
+| 0.1273        | 5.0   | 450  | 1.1057          | 0.7772   | 0.7436 | 0.6988    | 0.7945 |
+| 0.066         | 6.0   | 540  | 1.1990          | 0.7799   | 0.7168 | 0.7519    | 0.6849 |
+| 0.0286        | 7.0   | 630  | 1.2457          | 0.7994   | 0.7584 | 0.7434    | 0.7740 |
+| 0.0261        | 8.0   | 720  | 1.3297          | 0.7799   | 0.7106 | 0.7638    | 0.6644 |
+| 0.0097        | 9.0   | 810  | 1.3733          | 0.7855   | 0.7354 | 0.7379    | 0.7329 |
+| 0.0071        | 10.0  | 900  | 1.3693          | 0.7911   | 0.7440 | 0.7415    | 0.7466 |
+
+
+### Framework versions
+
+- Transformers 4.43.0.dev0
+- Pytorch 2.0.1+cu117
+- Datasets 2.19.1
+- Tokenizers 0.19.1

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