Advince/distilbert-base-uncased-lora-toxic-classification
Browse files- README.md +76 -0
- adapter_config.json +31 -0
- adapter_model.safetensors +3 -0
- runs/Sep25_17-20-16_da58eb7a1d54/events.out.tfevents.1727284817.da58eb7a1d54.620.0 +3 -0
- runs/Sep25_17-47-24_da58eb7a1d54/events.out.tfevents.1727286445.da58eb7a1d54.620.1 +3 -0
- runs/Sep25_17-50-04_da58eb7a1d54/events.out.tfevents.1727286605.da58eb7a1d54.620.2 +3 -0
- runs/Sep25_18-35-52_da58eb7a1d54/events.out.tfevents.1727289353.da58eb7a1d54.620.3 +3 -0
- runs/Sep25_18-36-44_da58eb7a1d54/events.out.tfevents.1727289405.da58eb7a1d54.620.4 +3 -0
- runs/Sep25_19-27-13_da58eb7a1d54/events.out.tfevents.1727292434.da58eb7a1d54.620.5 +3 -0
- runs/Sep25_19-33-07_da58eb7a1d54/events.out.tfevents.1727292787.da58eb7a1d54.620.6 +3 -0
- runs/Sep25_20-14-03_da58eb7a1d54/events.out.tfevents.1727295244.da58eb7a1d54.620.7 +3 -0
- special_tokens_map.json +7 -0
- tokenizer.json +0 -0
- tokenizer_config.json +56 -0
- training_args.bin +3 -0
- vocab.txt +0 -0
README.md
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---
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base_model: distilbert-base-uncased
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library_name: peft
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license: apache-2.0
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metrics:
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- accuracy
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tags:
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- generated_from_trainer
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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: 1.3115
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- Accuracy: {'accuracy': 0.8125}
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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: 15
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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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| No log | 1.0 | 431 | 0.6279 | {'accuracy': 0.7135416666666666} |
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| 0.7248 | 2.0 | 862 | 0.5949 | {'accuracy': 0.7604166666666666} |
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| 0.5433 | 3.0 | 1293 | 0.5986 | {'accuracy': 0.8072916666666666} |
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| 0.4762 | 4.0 | 1724 | 0.6967 | {'accuracy': 0.8125} |
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| 0.3971 | 5.0 | 2155 | 0.7136 | {'accuracy': 0.8229166666666666} |
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| 0.3471 | 6.0 | 2586 | 0.8597 | {'accuracy': 0.8177083333333334} |
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| 0.2695 | 7.0 | 3017 | 1.0061 | {'accuracy': 0.8072916666666666} |
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| 0.2695 | 8.0 | 3448 | 0.7674 | {'accuracy': 0.8333333333333334} |
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| 0.2417 | 9.0 | 3879 | 1.2479 | {'accuracy': 0.828125} |
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| 0.2079 | 10.0 | 4310 | 1.0548 | {'accuracy': 0.8177083333333334} |
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| 0.1941 | 11.0 | 4741 | 1.0516 | {'accuracy': 0.8229166666666666} |
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| 0.1711 | 12.0 | 5172 | 1.2246 | {'accuracy': 0.828125} |
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| 0.1253 | 13.0 | 5603 | 1.2416 | {'accuracy': 0.8177083333333334} |
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| 0.0918 | 14.0 | 6034 | 1.3199 | {'accuracy': 0.8229166666666666} |
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| 0.0918 | 15.0 | 6465 | 1.3115 | {'accuracy': 0.8125} |
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### Framework versions
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- PEFT 0.13.0
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- Transformers 4.44.2
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- Pytorch 2.4.1+cu121
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- Datasets 3.0.0
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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": "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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"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": 0.01,
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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": 4,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"q_lin"
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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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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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training_args.bin
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vocab.txt
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