End of training

README.md

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+---
+base_model: cardiffnlp/twitter-xlm-roberta-base-sentiment
+tags:
+- generated_from_trainer
+model-index:
+- name: XlM-roberta-AS-HU-f1-score
+  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. -->
+
+# XlM-roberta-AS-HU-f1-score
+
+This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1081
+- F1-score: 0.8389
+
+## 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 | F1-score |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.6852        | 1.0   | 64   | 0.6780          | 0.3697   |
+| 0.6514        | 2.0   | 128  | 0.5578          | 0.6958   |
+| 0.5075        | 3.0   | 192  | 0.5620          | 0.7619   |
+| 0.401         | 4.0   | 256  | 0.5068          | 0.7688   |
+| 0.2288        | 5.0   | 320  | 0.6490          | 0.8084   |
+| 0.1424        | 6.0   | 384  | 0.7662          | 0.8350   |
+| 0.0837        | 7.0   | 448  | 0.9138          | 0.8389   |
+| 0.0463        | 8.0   | 512  | 1.0355          | 0.8247   |
+| 0.0108        | 9.0   | 576  | 1.0874          | 0.8345   |
+| 0.0069        | 10.0  | 640  | 1.1081          | 0.8389   |
+
+
+### Framework versions
+
+- Transformers 4.41.1
+- Pytorch 2.0.1+cu117
+- Datasets 2.19.1
+- Tokenizers 0.19.1

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