djsull/intro_classification

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: skt/A.X-Encoder-base
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: hello_classification
+  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. -->
+
+# hello_classification
+
+This model is a fine-tuned version of [skt/A.X-Encoder-base](https://huggingface.co/skt/A.X-Encoder-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0077
+- Precision: 1.0
+- Recall: 0.9919
+- F1: 0.9959
+- Accuracy: 0.9983
+
+## 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: 128
+- eval_batch_size: 64
+- seed: 42
+- 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: 25
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 73   | 0.0225          | 0.9770    | 0.9860 | 0.9815 | 0.9931   |
+| No log        | 2.0   | 146  | 0.0194          | 0.9858    | 0.9721 | 0.9789 | 0.9923   |
+| No log        | 3.0   | 219  | 0.0147          | 0.9907    | 0.9860 | 0.9883 | 0.9957   |
+| No log        | 4.0   | 292  | 0.0182          | 0.9907    | 0.9907 | 0.9907 | 0.9966   |
+| No log        | 5.0   | 365  | 0.0144          | 0.9907    | 0.9860 | 0.9883 | 0.9957   |
+| No log        | 6.0   | 438  | 0.0139          | 0.9907    | 0.9860 | 0.9883 | 0.9957   |
+| 0.0144        | 7.0   | 511  | 0.0207          | 0.9907    | 0.9860 | 0.9883 | 0.9957   |
+| 0.0144        | 8.0   | 584  | 0.0183          | 0.9906    | 0.9814 | 0.9860 | 0.9948   |
+
+
+### Framework versions
+
+- Transformers 4.51.0
+- Pytorch 2.7.0+cu126
+- Tokenizers 0.21.2

added_tokens.json

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+}

config.json

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+{
+  "architectures": [
+    "ModernBertForSequenceClassification"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 0,
+  "classifier_activation": "gelu",
+  "classifier_bias": false,
+  "classifier_dropout": 0.0,
+  "classifier_pooling": "mean",
+  "cls_token_id": 0,
+  "decoder_bias": true,
+  "deterministic_flash_attn": false,
+  "embedding_dropout": 0.0,
+  "eos_token_id": 1,
+  "global_attn_every_n_layers": 3,
+  "global_rope_theta": 160000,
+  "gradient_checkpointing": false,
+  "hidden_activation": "gelu",
+  "hidden_size": 768,
+  "id2label": {
+    "0": "None",
+    "1": "hello"
+  },
+  "initializer_cutoff_factor": 2.0,
+  "initializer_range": 0.02,
+  "intermediate_size": 1152,
+  "label2id": {
+    "None": 0,
+    "hello": 1
+  },
+  "layer_norm_eps": 1e-05,
+  "local_attention": 128,
+  "local_rope_theta": 10000.0,
+  "max_position_embeddings": 16384,
+  "mlp_bias": false,
+  "mlp_dropout": 0.0,
+  "model_type": "modernbert",
+  "norm_bias": false,
+  "norm_eps": 1e-05,
+  "num_attention_heads": 12,
+  "num_hidden_layers": 22,
+  "pad_token_id": 49999,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "repad_logits_with_grad": false,
+  "sep_token_id": 1,
+  "sparse_pred_ignore_index": -100,
+  "sparse_prediction": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.51.0",
+  "vocab_size": 50000
+}

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tokenizer_config.json

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