16052025_xlm_roberta_large_test_linsearch_only_abstract

.gitattributes

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+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+library_name: transformers
+license: mit
+base_model: FacebookAI/xlm-roberta-large
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: 16052025_xlm_roberta_large_test_linsearch_only_abstract
+  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. -->
+
+# 16052025_xlm_roberta_large_test_linsearch_only_abstract
+
+This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.3318
+- Accuracy: 0.5931
+- F1 Macro: 0.5650
+- Precision Macro: 0.5755
+- Recall Macro: 0.5602
+
+## 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: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- 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_ratio: 0.1
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step  | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro |
+|:-------------:|:------:|:-----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|
+| 1.3362        | 0.9999 | 7024  | 1.3026          | 0.5520   | 0.4904   | 0.5266          | 0.4959       |
+| 1.2241        | 1.9999 | 14048 | 1.2036          | 0.5773   | 0.5348   | 0.5535          | 0.5395       |
+| 1.1337        | 2.9999 | 21072 | 1.1903          | 0.5760   | 0.5303   | 0.5466          | 0.5278       |
+| 1.069         | 3.9999 | 28096 | 1.1570          | 0.5876   | 0.5418   | 0.5564          | 0.5439       |
+| 0.9832        | 4.9999 | 35120 | 1.1723          | 0.5872   | 0.5461   | 0.5570          | 0.5461       |
+| 0.9197        | 5.9999 | 42144 | 1.1752          | 0.5871   | 0.5455   | 0.5456          | 0.5572       |
+| 0.8278        | 6.9999 | 49168 | 1.2078          | 0.5928   | 0.5537   | 0.5616          | 0.5589       |
+| 0.7568        | 7.9999 | 56192 | 1.2398          | 0.5923   | 0.5563   | 0.5612          | 0.5568       |
+| 0.6863        | 8.9999 | 63216 | 1.2840          | 0.5937   | 0.5556   | 0.5723          | 0.5465       |
+| 0.63          | 9.9999 | 70240 | 1.3318          | 0.5931   | 0.5650   | 0.5755          | 0.5602       |
+
+
+### Framework versions
+
+- Transformers 4.48.0
+- Pytorch 2.5.1+cu124
+- Datasets 3.2.0
+- Tokenizers 0.21.0

config.json

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+{
+  "_name_or_path": "FacebookAI/xlm-roberta-large",
+  "architectures": [
+    "XLMRobertaForSequenceClassification"
+  ],
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+  "bos_token_id": 0,
+  "classifier_dropout": null,
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+  "hidden_act": "gelu",
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+  "hidden_size": 1024,
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+    "1": "LABEL_1",
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+  "model_type": "xlm-roberta",
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+  "num_hidden_layers": 24,
+  "output_past": true,
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+  "vocab_size": 250002
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