xlm_roberta_large_test_linsearch_only_abstract

.gitattributes

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 *.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

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+---
+library_name: transformers
+license: mit
+base_model: xlm-roberta-large
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: 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. -->
+
+# xlm_roberta_large_test_linsearch_only_abstract
+
+This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.3502
+- Accuracy: 0.6550
+- F1 Macro: 0.6035
+- Precision Macro: 0.6172
+- Recall Macro: 0.5965
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Use OptimizerNames.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: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|
+| 1.1717        | 1.0   | 9861  | 1.1574          | 0.6366   | 0.5550   | 0.6017          | 0.5660       |
+| 1.0048        | 2.0   | 19722 | 1.0883          | 0.6559   | 0.5857   | 0.6034          | 0.5836       |
+| 0.9173        | 3.0   | 29583 | 1.1083          | 0.6550   | 0.5877   | 0.6266          | 0.5718       |
+| 0.8087        | 4.0   | 39444 | 1.1349          | 0.6569   | 0.5931   | 0.6144          | 0.5849       |
+| 0.6837        | 5.0   | 49305 | 1.2136          | 0.6592   | 0.6032   | 0.6173          | 0.5980       |
+| 0.5568        | 6.0   | 59166 | 1.3502          | 0.6550   | 0.6035   | 0.6172          | 0.5965       |
+| 0.4562        | 7.0   | 69027 | 1.6852          | 0.6512   | 0.6002   | 0.6104          | 0.5954       |
+| 0.3473        | 8.0   | 78888 | 2.0448          | 0.6443   | 0.6025   | 0.5993          | 0.6082       |
+| 0.2752        | 9.0   | 88749 | 2.4652          | 0.6478   | 0.5963   | 0.6014          | 0.5931       |
+| 0.1589        | 10.0  | 98610 | 2.6687          | 0.6449   | 0.6015   | 0.6056          | 0.5997       |
+
+
+### Framework versions
+
+- Transformers 4.50.1
+- Pytorch 2.5.1+cu121
+- Datasets 3.4.1
+- Tokenizers 0.21.1

config.json

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+  "eos_token_id": 2,
+  "hidden_act": "gelu",
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+  "hidden_size": 1024,
+  "id2label": {
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+  "vocab_size": 250002
+}

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