factual-consistency-multilabel-classification-ja

README.md

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+---
+license: apache-2.0
+base_model: line-corporation/line-distilbert-base-japanese
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: factual-consistency-multilabel-classification-ja
+  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. -->
+
+# factual-consistency-multilabel-classification-ja
+
+This model is a fine-tuned version of [line-corporation/line-distilbert-base-japanese](https://huggingface.co/line-corporation/line-distilbert-base-japanese) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4824
+- Accuracy: 0.7861
+
+## 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: 1e-05
+- train_batch_size: 64
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: tpu
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 306  | 0.4880          | 0.7861   |
+| 0.5189        | 2.0   | 612  | 0.4824          | 0.7861   |
+
+
+### Framework versions
+
+- Transformers 4.34.0
+- Pytorch 2.0.0+cu118
+- Datasets 2.14.5
+- Tokenizers 0.14.0