Training complete

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: bert-large-cased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: bert-large-cased-binary-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. -->
+
+# bert-large-cased-binary-classification
+
+This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1857
+- Accuracy: 0.7548
+- F1 Macro: 0.7312
+- Precision Macro: 0.7580
+- Recall Macro: 0.7246
+- Auc: 0.7883
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro | Auc    |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|:------:|
+| No log        | 1.0   | 79   | 0.6805          | 0.5987   | 0.3818   | 0.7987          | 0.5039       | 0.6079 |
+| No log        | 2.0   | 158  | 0.6254          | 0.6497   | 0.6490   | 0.6611          | 0.6655       | 0.7395 |
+| No log        | 3.0   | 237  | 0.6803          | 0.7166   | 0.6941   | 0.7087          | 0.6900       | 0.7563 |
+| No log        | 4.0   | 316  | 0.7502          | 0.7166   | 0.7106   | 0.7093          | 0.7153       | 0.7784 |
+| No log        | 5.0   | 395  | 1.1857          | 0.7548   | 0.7312   | 0.7580          | 0.7246       | 0.7883 |
+| No log        | 6.0   | 474  | 1.4866          | 0.7548   | 0.7312   | 0.7580          | 0.7246       | 0.7798 |
+| 0.3165        | 7.0   | 553  | 1.5617          | 0.7420   | 0.7319   | 0.7322          | 0.7316       | 0.7829 |
+| 0.3165        | 8.0   | 632  | 1.6626          | 0.7452   | 0.7311   | 0.7366          | 0.7280       | 0.7762 |
+| 0.3165        | 9.0   | 711  | 1.7303          | 0.7611   | 0.7423   | 0.7595          | 0.7363       | 0.7768 |
+| 0.3165        | 10.0  | 790  | 1.7471          | 0.7452   | 0.7294   | 0.7376          | 0.7255       | 0.7765 |
+
+
+### Framework versions
+
+- Transformers 4.57.1
+- Pytorch 2.8.0+cu126
+- Datasets 4.0.0
+- Tokenizers 0.22.1

config.json

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+{
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "directionality": "bidi",
+  "dtype": "float32",
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "pad_token_id": 0,
+  "pooler_fc_size": 768,
+  "pooler_num_attention_heads": 12,
+  "pooler_num_fc_layers": 3,
+  "pooler_size_per_head": 128,
+  "pooler_type": "first_token_transform",
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "transformers_version": "4.57.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 28996
+}

model.safetensors

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+size 1334372264

training_args.bin

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