loha_fine_tuned_rte_XLMroberta
Browse files- .gitattributes +1 -0
- README.md +71 -0
- adapter_config.json +26 -0
- adapter_model.safetensors +3 -0
- runs/May22_22-01-47_DESKTOP-22QTFDR/events.out.tfevents.1716408108.DESKTOP-22QTFDR.32492.0 +3 -0
- runs/May22_22-01-47_DESKTOP-22QTFDR/events.out.tfevents.1716408175.DESKTOP-22QTFDR.32492.1 +3 -0
- sentencepiece.bpe.model +3 -0
- special_tokens_map.json +15 -0
- tokenizer.json +3 -0
- tokenizer_config.json +54 -0
- training_args.bin +3 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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license: mit
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library_name: peft
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tags:
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- generated_from_trainer
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base_model: xlm-roberta-base
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metrics:
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- accuracy
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- f1
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model-index:
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- name: loha_fine_tuned_rte_XLMroberta
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# loha_fine_tuned_rte_XLMroberta
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6906
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- Accuracy: 0.6207
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- F1: 0.5466
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- training_steps: 400
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
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| 0.7061 | 1.7241 | 50 | 0.7021 | 0.4138 | 0.2422 |
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| 0.7012 | 3.4483 | 100 | 0.6955 | 0.4138 | 0.2422 |
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| 0.6902 | 5.1724 | 150 | 0.6970 | 0.4138 | 0.2422 |
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| 0.6922 | 6.8966 | 200 | 0.6917 | 0.5172 | 0.5087 |
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| 0.694 | 8.6207 | 250 | 0.6897 | 0.5862 | 0.4333 |
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| 0.6945 | 10.3448 | 300 | 0.6906 | 0.5517 | 0.4169 |
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| 0.6926 | 12.0690 | 350 | 0.6903 | 0.5862 | 0.4854 |
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| 0.6883 | 13.7931 | 400 | 0.6906 | 0.6207 | 0.5466 |
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### Framework versions
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- PEFT 0.11.1
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- Transformers 4.40.2
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- Pytorch 2.1.1+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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adapter_config.json
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{
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"alpha": 32,
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "xlm-roberta-base",
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"inference_mode": true,
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"init_weights": true,
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"layers_pattern": null,
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"layers_to_transform": null,
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"module_dropout": 0.0,
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"modules_to_save": [
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"classifier",
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"score"
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],
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"peft_type": "LOHA",
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"r": 16,
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"rank_dropout": 0.0,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"query",
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"value"
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],
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"task_type": "SEQ_CLS",
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"use_effective_conv2d": false
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}
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:bb86ea275dbb968fe8496431bc64c5f28173aa74fae3266177b73d6f269ee753
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size 7101032
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runs/May22_22-01-47_DESKTOP-22QTFDR/events.out.tfevents.1716408108.DESKTOP-22QTFDR.32492.0
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sentencepiece.bpe.model
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version https://git-lfs.github.com/spec/v1
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size 5069051
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special_tokens_map.json
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{
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"cls_token": "<s>",
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}
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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size 17082734
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tokenizer_config.json
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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