stackoverflow_tag_classification/modernBERT_vs_Deberta/deberta-v3-small/upbeat-panda-990

README.md

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+---
+library_name: transformers
+license: mit
+base_model: microsoft/deberta-v3-small
+tags:
+- generated_from_trainer
+model-index:
+- name: upbeat-panda-990
+  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. -->
+
+# upbeat-panda-990
+
+This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3377
+- Hamming Loss: 0.1123
+- Zero One Loss: 1.0
+- Jaccard Score: 1.0
+- Hamming Loss Optimised: 0.1123
+- Hamming Loss Threshold: 0.9000
+- Zero One Loss Optimised: 1.0
+- Zero One Loss Threshold: 0.9000
+- Jaccard Score Optimised: 1.0
+- Jaccard Score Threshold: 0.9000
+
+## 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: 2.9389019495075605e-06
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 2024
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.8827294021788243,0.966988814824775) and epsilon=1e-07 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 2
+
+### 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   | 400  | 0.3483          | 0.1123       | 1.0           | 1.0           | 0.1123                 | 0.9000                 | 1.0                     | 0.9000                  | 1.0                     | 0.9000                  |
+| 0.4547        | 2.0   | 800  | 0.3377          | 0.1123       | 1.0           | 1.0           | 0.1123                 | 0.9000                 | 1.0                     | 0.9000                  | 1.0                     | 0.9000                  |
+
+
+### Framework versions
+
+- Transformers 4.48.0.dev0
+- Pytorch 2.5.1+cu124
+- Datasets 3.1.0
+- Tokenizers 0.21.0

added_tokens.json

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+{
+  "[MASK]": 128000
+}

config.json

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+{
+  "_name_or_path": "microsoft/deberta-v3-small",
+  "architectures": [
+    "DebertaV2ForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "dictionary",
+    "1": "django",
+    "2": "list",
+    "3": "matplotlib",
+    "4": "numpy",
+    "5": "pandas",
+    "6": "python-2.7",
+    "7": "python-3.x",
+    "8": "regex",
+    "9": "string"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "dictionary": 0,
+    "django": 1,
+    "list": 2,
+    "matplotlib": 3,
+    "numpy": 4,
+    "pandas": 5,
+    "python-2.7": 6,
+    "python-3.x": 7,
+    "regex": 8,
+    "string": 9
+  },
+  "layer_norm_eps": 1e-07,
+  "legacy": true,
+  "max_position_embeddings": 512,
+  "max_relative_positions": -1,
+  "model_type": "deberta-v2",
+  "norm_rel_ebd": "layer_norm",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 6,
+  "pad_token_id": 0,
+  "pooler_dropout": 0,
+  "pooler_hidden_act": "gelu",
+  "pooler_hidden_size": 768,
+  "pos_att_type": [
+    "p2c",
+    "c2p"
+  ],
+  "position_biased_input": false,
+  "position_buckets": 256,
+  "problem_type": "multi_label_classification",
+  "relative_attention": true,
+  "share_att_key": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.48.0.dev0",
+  "type_vocab_size": 0,
+  "vocab_size": 128100
+}

model.safetensors

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special_tokens_map.json

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+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": {
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+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  }
+}

spm.model

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tokenizer_config.json

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+  "clean_up_tokenization_spaces": false,
+  "cls_token": "[CLS]",
+  "do_lower_case": false,
+  "eos_token": "[SEP]",
+  "extra_special_tokens": {},
+  "mask_token": "[MASK]",
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "sp_model_kwargs": {},
+  "split_by_punct": false,
+  "tokenizer_class": "DebertaV2Tokenizer",
+  "unk_token": "[UNK]",
+  "vocab_type": "spm"
+}

training_args.bin

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