kobert_model

README.md

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+---
+library_name: transformers
+base_model: monologg/koelectra-small-v3-discriminator
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: koelectra
+  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. -->
+
+# koelectra
+
+This model is a fine-tuned version of [monologg/koelectra-small-v3-discriminator](https://huggingface.co/monologg/koelectra-small-v3-discriminator) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5279
+- Accuracy: 0.7425
+
+## 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
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 100  | 0.6898          | 0.5925   |
+| No log        | 2.0   | 200  | 0.6713          | 0.6425   |
+| No log        | 3.0   | 300  | 0.6305          | 0.69     |
+| No log        | 4.0   | 400  | 0.5867          | 0.715    |
+| 0.6422        | 5.0   | 500  | 0.5630          | 0.7075   |
+| 0.6422        | 6.0   | 600  | 0.5326          | 0.745    |
+| 0.6422        | 7.0   | 700  | 0.5395          | 0.745    |
+| 0.6422        | 8.0   | 800  | 0.5281          | 0.7425   |
+| 0.6422        | 9.0   | 900  | 0.5445          | 0.7275   |
+| 0.4493        | 10.0  | 1000 | 0.5279          | 0.7425   |
+
+
+### Framework versions
+
+- Transformers 5.0.0
+- Pytorch 2.10.0+cu128
+- Datasets 4.0.0
+- Tokenizers 0.22.2

config.json

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+{
+  "add_cross_attention": false,
+  "architectures": [
+    "ElectraForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": null,
+  "classifier_dropout": null,
+  "dtype": "float32",
+  "embedding_size": 128,
+  "eos_token_id": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 256,
+  "initializer_range": 0.02,
+  "intermediate_size": 1024,
+  "is_decoder": false,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "electra",
+  "num_attention_heads": 4,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "problem_type": "single_label_classification",
+  "summary_activation": "gelu",
+  "summary_last_dropout": 0.1,
+  "summary_type": "first",
+  "summary_use_proj": true,
+  "tie_word_embeddings": true,
+  "transformers_version": "5.0.0",
+  "type_vocab_size": 2,
+  "use_cache": false,
+  "vocab_size": 35000
+}

model.safetensors

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+oid sha256:9ae5c343525a4d48dbcde81606bae86deb2f04bdad5ddb8074cb374c23faf401
+size 56513912

training_args.bin

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