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-detests
+  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-detests
+
+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: 1.2413
+- Accuracy: 0.8396
+- F1-score: 0.7695
+- Precision: 0.7724
+- Recall: 0.7668
+- Auc: 0.7668
+
+## 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    |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|:------:|
+| 0.3772        | 1.0   | 174  | 0.4358          | 0.8298   | 0.6814   | 0.8246    | 0.6513 | 0.6513 |
+| 0.1092        | 2.0   | 348  | 0.4312          | 0.8625   | 0.7925   | 0.8139    | 0.7765 | 0.7765 |
+| 0.0955        | 3.0   | 522  | 0.7126          | 0.8412   | 0.7724   | 0.7746    | 0.7704 | 0.7704 |
+| 0.0625        | 4.0   | 696  | 0.9681          | 0.8412   | 0.7688   | 0.7757    | 0.7627 | 0.7627 |
+| 0.0056        | 5.0   | 870  | 1.1017          | 0.8347   | 0.7567   | 0.7666    | 0.7484 | 0.7484 |
+| 0.0018        | 6.0   | 1044 | 1.2244          | 0.8347   | 0.7630   | 0.7651    | 0.7610 | 0.7610 |
+| 0.0001        | 7.0   | 1218 | 1.2190          | 0.8412   | 0.7637   | 0.7778    | 0.7526 | 0.7526 |
+| 0.0001        | 8.0   | 1392 | 1.2356          | 0.8396   | 0.7645   | 0.7739    | 0.7566 | 0.7566 |
+| 0.0001        | 9.0   | 1566 | 1.2332          | 0.8380   | 0.7547   | 0.7746    | 0.7403 | 0.7403 |
+| 0.0001        | 10.0  | 1740 | 1.2413          | 0.8396   | 0.7695   | 0.7724    | 0.7668 | 0.7668 |
+
+
+### Framework versions
+
+- Transformers 4.33.1
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3

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