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 +1,69 @@
+---
+library_name: transformers
+license: mit
+base_model: FacebookAI/xlm-roberta-large
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: xlmr_immigration_combo15_3
+  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. -->
+
+# xlmr_immigration_combo15_3
+
+This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2712
+- Accuracy: 0.9332
+- 1-f1: 0.8980
+- 1-recall: 0.8842
+- 1-precision: 0.9124
+- Balanced Acc: 0.9209
+
+## 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: 128
+- eval_batch_size: 128
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 15
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1   | 1-recall | 1-precision | Balanced Acc |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
+| 0.1474        | 1.0   | 25   | 0.2366          | 0.9306   | 0.8977 | 0.9151   | 0.8810      | 0.9267       |
+| 0.1345        | 2.0   | 50   | 0.2140          | 0.9383   | 0.9024 | 0.8571   | 0.9528      | 0.9180       |
+| 0.1144        | 3.0   | 75   | 0.2228          | 0.9357   | 0.9004 | 0.8726   | 0.9300      | 0.9199       |
+| 0.1508        | 4.0   | 100  | 0.2712          | 0.9332   | 0.8980 | 0.8842   | 0.9124      | 0.9209       |
+
+
+### Framework versions
+
+- Transformers 4.56.0.dev0
+- Pytorch 2.8.0+cu126
+- Datasets 4.0.0
+- Tokenizers 0.21.4

config.json

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+  "architectures": [
+    "XLMRobertaForSequenceClassification"
+  ],
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+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "xlm-roberta",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.56.0.dev0",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

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runs/Aug20_15-28-47_d73683511505/events.out.tfevents.1755703728.d73683511505.390.3

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special_tokens_map.json

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tokenizer_config.json

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