lora_fine_tuned_cb_XLMroberta
Browse files- .gitattributes +1 -0
- README.md +71 -0
- adapter_config.json +32 -0
- adapter_model.safetensors +3 -0
- runs/May20_08-04-40_9b9f000fd261/events.out.tfevents.1716192280.9b9f000fd261.221.0 +3 -0
- runs/May20_08-04-40_9b9f000fd261/events.out.tfevents.1716194986.9b9f000fd261.221.1 +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: lora_fine_tuned_cb_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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# lora_fine_tuned_cb_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: 1.4225
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- Accuracy: 0.3182
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- F1: 0.1536
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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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| 0.9083 | 3.5714 | 50 | 1.2624 | 0.3182 | 0.1536 |
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| 0.7455 | 7.1429 | 100 | 1.4585 | 0.3182 | 0.1536 |
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| 0.7714 | 10.7143 | 150 | 1.4354 | 0.3182 | 0.1536 |
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| 0.721 | 14.2857 | 200 | 1.3749 | 0.3182 | 0.1536 |
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| 0.7302 | 17.8571 | 250 | 1.4032 | 0.3182 | 0.1536 |
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| 0.7313 | 21.4286 | 300 | 1.4237 | 0.3182 | 0.1536 |
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| 0.6958 | 25.0 | 350 | 1.4302 | 0.3182 | 0.1536 |
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| 0.7295 | 28.5714 | 400 | 1.4225 | 0.3182 | 0.1536 |
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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 2.2.1+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_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "xlm-roberta-base",
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 32,
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"lora_dropout": 0.0,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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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": "LORA",
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"r": 16,
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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_dora": false,
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"use_rslora": false
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}
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adapter_model.safetensors
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runs/May20_08-04-40_9b9f000fd261/events.out.tfevents.1716192280.9b9f000fd261.221.0
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runs/May20_08-04-40_9b9f000fd261/events.out.tfevents.1716194986.9b9f000fd261.221.1
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sentencepiece.bpe.model
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version https://git-lfs.github.com/spec/v1
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special_tokens_map.json
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{
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"bos_token": "<s>",
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"cls_token": "<s>",
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"lstrip": true,
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"unk_token": "<unk>"
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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tokenizer_config.json
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}
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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size 4984
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