End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: microsoft/deberta-v3-large
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: wikidyk-scope-clf-deberta-v3-large-1_cluster
+  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. -->
+
+# wikidyk-scope-clf-deberta-v3-large-1_cluster
+
+This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.5455
+- Accuracy: 0.8204
+- F1: 0.8462
+- Precision: 0.8141
+- Recall: 0.8808
+
+## 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: 2e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- total_train_batch_size: 128
+- total_eval_batch_size: 128
+- optimizer: Use 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: 10.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.0921        | 1.0   | 902  | 0.6758          | 0.7565   | 0.7654 | 0.8326    | 0.7082 |
+| 0.0634        | 2.0   | 1804 | 0.7185          | 0.8174   | 0.8362 | 0.8414    | 0.8310 |
+| 0.0212        | 3.0   | 2706 | 0.9475          | 0.7725   | 0.8024 | 0.7821    | 0.8238 |
+| 0.0079        | 4.0   | 3608 | 1.2432          | 0.7445   | 0.7991 | 0.7149    | 0.9057 |
+| 0.0021        | 5.0   | 4510 | 1.4449          | 0.8024   | 0.8339 | 0.7889    | 0.8843 |
+| 0.0003        | 6.0   | 5412 | 1.3861          | 0.7934   | 0.8262 | 0.7822    | 0.8754 |
+| 0.0001        | 7.0   | 6314 | 1.5118          | 0.7934   | 0.8265 | 0.7813    | 0.8772 |
+| 0.0058        | 8.0   | 7216 | 1.8437          | 0.7475   | 0.8019 | 0.7161    | 0.9110 |
+| 0.0002        | 9.0   | 8118 | 1.6242          | 0.7874   | 0.8253 | 0.7656    | 0.8950 |
+| 0.0037        | 10.0  | 9020 | 1.5455          | 0.8204   | 0.8462 | 0.8141    | 0.8808 |
+
+
+### Framework versions
+
+- Transformers 4.51.3
+- Pytorch 2.6.0+cu124
+- Datasets 3.5.1
+- Tokenizers 0.21.1

added_tokens.json

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

config.json

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+{
+  "architectures": [
+    "DebertaV2ForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": 0
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "label2id": {
+    "0": 0
+  },
+  "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": 16,
+  "num_hidden_layers": 24,
+  "pad_token_id": 0,
+  "pooler_dropout": 0,
+  "pooler_hidden_act": "gelu",
+  "pooler_hidden_size": 1024,
+  "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": "4.51.3",
+  "type_vocab_size": 0,
+  "vocab_size": 128100
+}

model.safetensors

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special_tokens_map.json

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+    "lstrip": false,
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+}

spm.model

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tokenizer_config.json

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+  "clean_up_tokenization_spaces": false,
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+  "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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