End of training

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,76 @@
+---
+library_name: transformers
+license: mit
+base_model: xlm-roberta-large
+tags:
+- generated_from_trainer
+datasets:
+- generator
+metrics:
+- accuracy
+model-index:
+- name: XLM-RoBERTa-1
+  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-1
+
+This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the generator dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4935
+- Accuracy: 0.9044
+- Micro Precision: 0.9044
+- Micro Recall: 0.9044
+- Micro F1: 0.9044
+- Macro Precision: 0.8822
+- Macro Recall: 0.8527
+- Macro F1: 0.8599
+
+## 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: 1e-05
+- train_batch_size: 12
+- eval_batch_size: 12
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 24
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch  | Step   | Validation Loss | Accuracy | Micro Precision | Micro Recall | Micro F1 | Macro Precision | Macro Recall | Macro F1 |
+|:-------------:|:------:|:------:|:---------------:|:--------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------:|
+| 0.3304        | 1.0000 | 40166  | 0.3911          | 0.8883   | 0.8883          | 0.8883       | 0.8883   | 0.8651          | 0.8285       | 0.8359   |
+| 0.2376        | 2.0    | 80333  | 0.3998          | 0.9014   | 0.9014          | 0.9014       | 0.9014   | 0.8714          | 0.8480       | 0.8523   |
+| 0.1733        | 3.0000 | 120499 | 0.4297          | 0.9059   | 0.9059          | 0.9059       | 0.9059   | 0.8718          | 0.8607       | 0.8610   |
+| 0.1268        | 4.0    | 160666 | 0.4822          | 0.9088   | 0.9088          | 0.9088       | 0.9088   | 0.8807          | 0.8608       | 0.8649   |
+| 0.1038        | 4.9999 | 200830 | 0.5242          | 0.9087   | 0.9087          | 0.9087       | 0.9087   | 0.8753          | 0.8646       | 0.8660   |
+
+
+### Framework versions
+
+- Transformers 4.46.2
+- Pytorch 2.5.1+cu124
+- Datasets 3.1.0
+- Tokenizers 0.20.3

config.json

@@ -0,0 +1,160 @@
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