End of training

README.md

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+---
+license: mit
+base_model: papluca/xlm-roberta-base-language-detection
+tags:
+- generated_from_trainer
+metrics:
+- f1
+model-index:
+- name: xlm-roberta-base-language-detection-disaster-twitter
+  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-base-language-detection-disaster-twitter
+
+This model is a fine-tuned version of [papluca/xlm-roberta-base-language-detection](https://huggingface.co/papluca/xlm-roberta-base-language-detection) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4869
+- F1: 0.7902
+
+## 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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| No log        | 1.0   | 381  | 0.4407          | 0.7701 |
+| 0.4972        | 2.0   | 762  | 0.4186          | 0.7560 |
+| 0.3742        | 3.0   | 1143 | 0.4869          | 0.7902 |
+
+
+### Framework versions
+
+- Transformers 4.38.1
+- Pytorch 2.1.2+cpu
+- Datasets 2.1.0
+- Tokenizers 0.15.2

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