stackoverflow_tag_classification/initial_run/bert-base-cased/beautiful-worm-91

README.md

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+---
+library_name: peft
+license: apache-2.0
+base_model: google-bert/bert-base-cased
+tags:
+- generated_from_trainer
+model-index:
+- name: beautiful-worm-91
+  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. -->
+
+# beautiful-worm-91
+
+This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5762
+- Hamming Loss: 0.2815
+- Zero One Loss: 1.0
+- Jaccard Score: 0.8606
+- Hamming Loss Optimised: 0.1121
+- Hamming Loss Threshold: 0.7112
+- Zero One Loss Optimised: 0.8762
+- Zero One Loss Threshold: 0.5937
+- Jaccard Score Optimised: 0.8487
+- Jaccard Score Threshold: 0.3892
+
+## 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: 1.27612271859294e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 2024
+- 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
+- num_epochs: 7
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Hamming Loss | Zero One Loss | Jaccard Score | Hamming Loss Optimised | Hamming Loss Threshold | Zero One Loss Optimised | Zero One Loss Threshold | Jaccard Score Optimised | Jaccard Score Threshold |
+|:-------------:|:-----:|:----:|:---------------:|:------------:|:-------------:|:-------------:|:----------------------:|:----------------------:|:-----------------------:|:-----------------------:|:-----------------------:|:-----------------------:|
+| No log        | 1.0   | 100  | 0.7158          | 0.4196       | 1.0           | 0.8558        | 0.1123                 | 0.7884                 | 0.8688                  | 0.7125                  | 0.8208                  | 0.5703                  |
+| No log        | 2.0   | 200  | 0.6802          | 0.3589       | 1.0           | 0.8562        | 0.1123                 | 0.8010                 | 0.89                    | 0.6870                  | 0.8545                  | 0.5943                  |
+| No log        | 3.0   | 300  | 0.6461          | 0.3409       | 1.0           | 0.8701        | 0.1121                 | 0.7495                 | 0.885                   | 0.6670                  | 0.8457                  | 0.6441                  |
+| No log        | 4.0   | 400  | 0.6162          | 0.3392       | 1.0           | 0.8767        | 0.1123                 | 0.7474                 | 0.8812                  | 0.6319                  | 0.8506                  | 0.4177                  |
+| 0.6723        | 5.0   | 500  | 0.5936          | 0.3326       | 1.0           | 0.8785        | 0.1121                 | 0.7112                 | 0.8775                  | 0.6089                  | 0.8457                  | 0.6006                  |
+| 0.6723        | 6.0   | 600  | 0.5804          | 0.2973       | 1.0           | 0.8651        | 0.1121                 | 0.7112                 | 0.875                   | 0.5979                  | 0.8447                  | 0.5836                  |
+| 0.6723        | 7.0   | 700  | 0.5762          | 0.2815       | 1.0           | 0.8606        | 0.1121                 | 0.7112                 | 0.8762                  | 0.5937                  | 0.8487                  | 0.3892                  |
+
+
+### Framework versions
+
+- PEFT 0.13.2
+- Transformers 4.47.0
+- Pytorch 2.5.1+cu124
+- Datasets 3.1.0
+- Tokenizers 0.21.0

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": {
+    "base_model_class": "BertForSequenceClassification",
+    "parent_library": "transformers.models.bert.modeling_bert"
+  },
+  "base_model_name_or_path": "google-bert/bert-base-cased",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 21,
+  "lora_dropout": 0,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 4,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "value",
+    "query"
+  ],
+  "task_type": null,
+  "use_dora": true,
+  "use_rslora": false
+}

adapter_model.safetensors

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special_tokens_map.json

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+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "[CLS]",
+  "do_lower_case": false,
+  "extra_special_tokens": {},
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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