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paduraru2009/distilbert-base-uncased-sentimentanalysis-demo
Browse files- README.md +69 -0
- adapter_config.json +23 -0
- adapter_model.bin +3 -0
- special_tokens_map.json +7 -0
- tokenizer.json +0 -0
- tokenizer_config.json +14 -0
- training_args.bin +3 -0
- vocab.txt +0 -0
README.md
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---
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license: apache-2.0
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base_model: distilbert-base-uncased
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: distilbert-base-uncased-lora-text-classification
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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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# distilbert-base-uncased-lora-text-classification
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5479
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- Accuracy: {'accuracy': 0.7540666666666667}
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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: 0.001
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- train_batch_size: 4
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- eval_batch_size: 4
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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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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:--------------------------------:|
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| 0.6425 | 1.0 | 7500 | 0.5937 | {'accuracy': 0.8124} |
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| 0.6312 | 2.0 | 15000 | 0.6853 | {'accuracy': 0.6939} |
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| 0.6127 | 3.0 | 22500 | 0.5976 | {'accuracy': 0.7106333333333333} |
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| 0.6043 | 4.0 | 30000 | 0.5694 | {'accuracy': 0.7357} |
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| 0.5742 | 5.0 | 37500 | 0.6108 | {'accuracy': 0.7456333333333334} |
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| 0.5527 | 6.0 | 45000 | 0.5915 | {'accuracy': 0.7628333333333334} |
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| 0.615 | 7.0 | 52500 | 0.5992 | {'accuracy': 0.7109333333333333} |
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| 0.5847 | 8.0 | 60000 | 0.5428 | {'accuracy': 0.7357333333333334} |
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| 0.5767 | 9.0 | 67500 | 0.5650 | {'accuracy': 0.7488333333333334} |
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| 0.5463 | 10.0 | 75000 | 0.5479 | {'accuracy': 0.7540666666666667} |
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### Framework versions
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- Transformers 4.32.1
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- Pytorch 2.1.0+cu121
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- Datasets 2.14.6
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- Tokenizers 0.13.2
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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": "distilbert-base-uncased",
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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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"layers_pattern": null,
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"layers_to_transform": null,
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"lora_alpha": 32,
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"lora_dropout": 0.01,
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 4,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"v_lin",
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"q_lin"
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],
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"task_type": "SEQ_CLS"
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}
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adapter_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:50732b4f60cc53eb80b82376f94647567ab4577f778b706ac86550d20c4803eb
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size 2673602
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special_tokens_map.json
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{
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"cls_token": "[CLS]",
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"mask_token": "[MASK]",
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"unk_token": "[UNK]"
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}
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tokenizer.json
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tokenizer_config.json
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{
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"add_prefix_space": true,
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"clean_up_tokenization_spaces": true,
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"cls_token": "[CLS]",
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"do_lower_case": true,
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "DistilBertTokenizer",
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"unk_token": "[UNK]"
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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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oid sha256:1b0f386383755b70794e1581e72fde2132b94a2577fd8de37914815c943a0c49
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size 4536
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vocab.txt
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