End of training

README.md

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+---
+base_model: finiteautomata/beto-sentiment-analysis
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+model-index:
+- name: beto-sentiment-analysis-finetuned-detests24
+  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. -->
+
+# beto-sentiment-analysis-finetuned-detests24
+
+This model is a fine-tuned version of [finiteautomata/beto-sentiment-analysis](https://huggingface.co/finiteautomata/beto-sentiment-analysis) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0647
+- Accuracy: 0.8609
+- F1-score: 0.7906
+- Precision: 0.8107
+- Recall: 0.7755
+- Auc: 0.7755
+
+## 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-score | Precision | Recall | Auc    |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|:------:|
+| 0.4035        | 1.0   | 153  | 0.3459          | 0.8527   | 0.7540   | 0.8257    | 0.7219 | 0.7219 |
+| 0.2217        | 2.0   | 306  | 0.4773          | 0.8183   | 0.7700   | 0.7519    | 0.8088 | 0.8088 |
+| 0.0787        | 3.0   | 459  | 0.6757          | 0.8576   | 0.7959   | 0.7982    | 0.7936 | 0.7936 |
+| 0.016         | 4.0   | 612  | 0.7801          | 0.8478   | 0.7851   | 0.7830    | 0.7873 | 0.7873 |
+| 0.0251        | 5.0   | 765  | 0.9783          | 0.8511   | 0.7994   | 0.7862    | 0.8173 | 0.8173 |
+| 0.0159        | 6.0   | 918  | 0.9841          | 0.8576   | 0.7926   | 0.8001    | 0.7860 | 0.7860 |
+| 0.0002        | 7.0   | 1071 | 0.9943          | 0.8609   | 0.7906   | 0.8107    | 0.7755 | 0.7755 |
+| 0.0001        | 8.0   | 1224 | 1.0252          | 0.8625   | 0.7925   | 0.8139    | 0.7765 | 0.7765 |
+| 0.0013        | 9.0   | 1377 | 1.0663          | 0.8511   | 0.7808   | 0.7916    | 0.7716 | 0.7716 |
+| 0.0001        | 10.0  | 1530 | 1.0647          | 0.8609   | 0.7906   | 0.8107    | 0.7755 | 0.7755 |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.17.0
+- Tokenizers 0.15.1

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